A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

ADJUSTED_R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression

Indicates (adjusted ) criterion regression.

AFTER_SUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta

Used by method examineStep to indicate examining after a successful step

AFTER_UNSUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta

Used by method examineStep to indicate examining after an unsuccessful step

ALPHA_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis

Indicates alpha factor analysis.

ANNUAL - Static variable in class com.imsl.finance.Bond

Coupon payments are made annually.

ANOVA - class com.imsl.stat.ANOVA.

Analysis of Variance table and related statistics.

ANOVA(double[][]) - Constructor for class com.imsl.stat.ANOVA

Analyzes a one-way classification model.

ANOVA(double, double, double, double, double) - Constructor for class com.imsl.stat.ANOVA

Construct an analysis of variance table and related statistics.

ANOVAFactorial - class com.imsl.stat.ANOVAFactorial.

Analyzes a balanced factorial design with fixed effects.

ANOVAFactorial(int, int[], double[]) - Constructor for class com.imsl.stat.ANOVAFactorial

Constructor for ANOVAFactorial.

ARMA - class com.imsl.stat.ARMA.

Computes least-square estimates of parameters for an ARMA model.

ARMA(int, int, double[]) - Constructor for class com.imsl.stat.ARMA

Constructor for ARMA.

ARMA.IllConditionedException - exception com.imsl.stat.ARMA.IllConditionedException.

The problem is ill-conditioned.

ARMA.IllConditionedException(String) - Constructor for class com.imsl.stat.ARMA.IllConditionedException

Constructs an IllConditionedException with the specified detail message.

ARMA.IllConditionedException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.IllConditionedException

Constructs an IllConditionedException with the specified detail message.

ARMA.IncreaseErrRelException - exception com.imsl.stat.ARMA.IncreaseErrRelException.

The bound for the relative error is too small.

ARMA.IncreaseErrRelException(String) - Constructor for class com.imsl.stat.ARMA.IncreaseErrRelException

Constructs an IncreaseErrRelException with the specified detail message.

ARMA.IncreaseErrRelException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.IncreaseErrRelException

Constructs an IncreaseErrRelException with the specified detail message.

ARMA.MatrixSingularException - exception com.imsl.stat.ARMA.MatrixSingularException.

The input matrix is singular.

ARMA.MatrixSingularException(String) - Constructor for class com.imsl.stat.ARMA.MatrixSingularException

Constructs an MatrixSingularException with the specified detail message.

ARMA.MatrixSingularException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.MatrixSingularException

Constructs an MatrixSingularException with the specified detail message.

ARMA.NewInitialGuessException - exception com.imsl.stat.ARMA.NewInitialGuessException.

The iteration has not made good progress.

ARMA.NewInitialGuessException(String) - Constructor for class com.imsl.stat.ARMA.NewInitialGuessException

Constructs an NewInitialGuessException with the specified detail message.

ARMA.NewInitialGuessException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.NewInitialGuessException

Constructs an NewInitialGuessException with the specified detail message.

ARMA.TooManyCallsException - exception com.imsl.stat.ARMA.TooManyCallsException.

The number of calls to the function has exceeded the maximum number of iterations.

ARMA.TooManyCallsException(String) - Constructor for class com.imsl.stat.ARMA.TooManyCallsException

Constructs an TooManyCallsException with the specified detail message.

ARMA.TooManyCallsException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyCallsException

Constructs an TooManyCallsException with the specified detail message.

ARMA.TooManyFcnEvalException - exception com.imsl.stat.ARMA.TooManyFcnEvalException.

Maximum number of function evaluations exceeded.

ARMA.TooManyFcnEvalException(String) - Constructor for class com.imsl.stat.ARMA.TooManyFcnEvalException

Constructs an TooManyFcnEvalException with the specified detail message.

ARMA.TooManyFcnEvalException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyFcnEvalException

Constructs an TooManyFcnEvalException with the specified detail message.

ARMA.TooManyITNException - exception com.imsl.stat.ARMA.TooManyITNException.

Maximum number of iterations exceeded.

ARMA.TooManyITNException(String) - Constructor for class com.imsl.stat.ARMA.TooManyITNException

Constructs an TooManyITNException with the specified detail message.

ARMA.TooManyITNException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyITNException

ARMA.TooManyJacobianEvalException - exception com.imsl.stat.ARMA.TooManyJacobianEvalException.

Maximum number of Jacobian evaluations exceeded.

ARMA.TooManyJacobianEvalException(String) - Constructor for class com.imsl.stat.ARMA.TooManyJacobianEvalException

Constructs an TooManyJacobianEvalException with the specified detail message.

ARMA.TooManyJacobianEvalException(String, Object[]) - Constructor for class com.imsl.stat.ARMA.TooManyJacobianEvalException

Constructs an TooManyJacobianEvalException with the specified detail message.

AT_BEGINNING_OF_PERIOD - Static variable in class com.imsl.finance.Finance

Flag used to indicate that payment is made at the beginning of each period.

AT_END_OF_PERIOD - Static variable in class com.imsl.finance.Finance

Flag used to indicate that payment is made at the end of each period.

AUTOSCALE_DATA - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that autoscaling is to be done by scanning the data nodes.

AUTOSCALE_DENSITY - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that autoscaling is to adjust the "Density" attribute.

AUTOSCALE_NUMBER - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that autoscaling is to adjust the "Number" attribute.

AUTOSCALE_OFF - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that autoscaling is turned off.

AUTOSCALE_WINDOW - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that autoscaling is to be done by using the "Window" attribute.

AXIS_X - Static variable in class com.imsl.chart.ChartNode

Flag to indicate x-axis.

AXIS_X_TOP - Static variable in class com.imsl.chart.ChartNode

Flag to indicate x-axis placed on top of the chart.

AXIS_Y - Static variable in class com.imsl.chart.ChartNode

Flag to indicate y-axis.

AXIS_Y_RIGHT - Static variable in class com.imsl.chart.ChartNode

Flag to indicate y-axis placed to the right of the chart.

AbstractFlatFile - class com.imsl.io.AbstractFlatFile.

Reads a text or binary file as a ResultSet.

AbstractFlatFile() - Constructor for class com.imsl.io.AbstractFlatFile

Initializes an AbstractFlatFile.

AbstractFlatFile.FlatFileSQLException - exception com.imsl.io.AbstractFlatFile.FlatFileSQLException.

A SQLException thrown by the AbstractFlatFile class.

Activation - interface com.imsl.datamining.neural.Activation.

Interface implemented by perceptron activation functions.

AutoCorrelation - class com.imsl.stat.AutoCorrelation.

Computes the sample autocorrelation function of a stationary time series.

AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.AutoCorrelation

Constructor to compute the sample autocorrelation function of a stationary time series.

AutoCorrelation.NonPosVariancesException - exception com.imsl.stat.AutoCorrelation.NonPosVariancesException.

The problem is ill-conditioned.

AutoCorrelation.NonPosVariancesException(String) - Constructor for class com.imsl.stat.AutoCorrelation.NonPosVariancesException

Constructs an NonPosVariancesException with the specified detail message.

AutoCorrelation.NonPosVariancesException(String, Object[]) - Constructor for class com.imsl.stat.AutoCorrelation.NonPosVariancesException

Constructs an NonPosVariancesException with the specified detail message.

Axis - class com.imsl.chart.Axis.

The Axis node provides the mapping for all of its children from the user coordinate space to the device (screen) space.

Axis(Chart) - Constructor for class com.imsl.chart.Axis

Contructs an Axis node.

Axis1D - class com.imsl.chart.Axis1D.

An x-axis or a y-axis.

AxisLabel - class com.imsl.chart.AxisLabel.

The labels on an axis.

AxisLine - class com.imsl.chart.AxisLine.

The axis line.

AxisR - class com.imsl.chart.AxisR.

The R-axis in a polar plot.

AxisRLabel - class com.imsl.chart.AxisRLabel.

The labels on an axis.

AxisRLine - class com.imsl.chart.AxisRLine.

The radius axis line in a polar plot.

AxisRMajorTick - class com.imsl.chart.AxisRMajorTick.

The major tick marks for the radius axis in a polar plot.

AxisTheta - class com.imsl.chart.AxisTheta.

The angular axis in a polar plot.

AxisTitle - class com.imsl.chart.AxisTitle.

The title on an axis.

AxisUnit - class com.imsl.chart.AxisUnit.

The unit title on an axis.

AxisXY - class com.imsl.chart.AxisXY.

The axes for an x-y chart.

AxisXY(Chart) - Constructor for class com.imsl.chart.AxisXY

Create an AxisXY.

abs(Complex) - Static method in class com.imsl.math.Complex

Returns the absolute value (modulus) of a Complex, |z|.

abs(int) - Static method in class com.imsl.math.JMath

Returns the absolute value of an int.

abs(long) - Static method in class com.imsl.math.JMath

Returns the absolute value of a long.

abs(float) - Static method in class com.imsl.math.JMath

Returns the absolute value of a float.

abs(double) - Static method in class com.imsl.math.JMath

Returns the absolute value of a double.

absolute(int) - Method in class com.imsl.io.AbstractFlatFile

Moves the cursor to the given row number in this ResultSet object.

accrint(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the interest which has accrued on a security that pays interest periodically.

accrintm(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the interest which has accrued on a security that pays interest at maturity.

acos(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse cosine (arc cosine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.

acos(double) - Static method in class com.imsl.math.JMath

Returns the inverse (arc) cosine of a double.

acosh(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse hyperbolic cosine (arc cosh) of a Complex, with a branch cut at values less than one along the real axis.

acosh(double) - Static method in class com.imsl.math.Hyperbolic

Returns the inverse hyperbolic cosine of its argument.

add(Complex, Complex) - Static method in class com.imsl.math.Complex

Returns the sum of two Complex objects, x+y.

add(Complex, double) - Static method in class com.imsl.math.Complex

Returns the sum of a Complex and a double, x+y.

add(double, Complex) - Static method in class com.imsl.math.Complex

Returns the sum of a double and a Complex, x+y.

add(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Add two rectangular Complex arrays, a + b.

add(double[][], double[][]) - Static method in class com.imsl.math.Matrix

Add two rectangular arrays, a + b.

add(Physical, Physical) - Static method in class com.imsl.math.Physical

Add two compatible Physical objects.

addLegendItem(int, ChartNode) - Method in class com.imsl.chart.Chart

Adds a legend to this ChartNode

addMouseListener(MouseListener) - Method in class com.imsl.chart.Chart

Adds a MouseListener to the component associated with this chart.

addMouseMotionListener(MouseMotionListener) - Method in class com.imsl.chart.Chart

Adds a MouseMotionListener to the component associated with this chart.

addNode(Node) - Method in class com.imsl.datamining.neural.Layer

Associates a Perceptron with this Layer.

addPickListener(PickListener) - Method in class com.imsl.chart.ChartNode

Adds a PickListener to this node.

afterLast() - Method in class com.imsl.io.AbstractFlatFile

Moves the cursor to the end of this ResultSet object, just after the last row.

allConverged() - Method in class com.imsl.math.ZeroFunction

Returns true if the iterations for all of the roots have converged.

amordegrc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the depreciation for each accounting period.

amorlinc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the depreciation for each accounting period.

argument(Complex) - Static method in class com.imsl.math.Complex

Returns the argument (phase) of a Complex, in radians, with a branch cut along the negative real axis.

ascending(double[], int[]) - Static method in class com.imsl.stat.Sort

Sort an array into ascending order.

ascending(int[], int[]) - Static method in class com.imsl.stat.Sort

Sort an array into ascending order.

ascending(double[]) - Static method in class com.imsl.stat.Sort

Sort an array into ascending order.

ascending(int[]) - Static method in class com.imsl.stat.Sort

Function to sort an integer array into ascending order.

ascending(double[][], int) - Static method in class com.imsl.stat.Sort

Sort a matrix into ascending order by specified keys.

ascending(double[][], int[]) - Static method in class com.imsl.stat.Sort

Sort a matrix into ascending order by specified keys.

ascending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort

Sort an array into ascending order by specified keys.

ascending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort

Sort a matrix into ascending order by specified keys.

asin(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse sine (arc sine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.

asin(double) - Static method in class com.imsl.math.JMath

Returns the inverse (arc) sine of a double.

asinh(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse hyperbolic sine (arc sinh) of a Complex, with branch cuts outside the interval [-i,i].

asinh(double) - Static method in class com.imsl.math.Hyperbolic

Returns the inverse hyperbolic sine of its argument.

atan(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse tangent (arc tangent) of a Complex, with branch cuts outside the interval [-i,i] along the imaginary axis.

atan(double) - Static method in class com.imsl.math.JMath

Returns the inverse (arc) tangent of a double.

atan2(double, double) - Static method in class com.imsl.math.JMath

Returns the angle corresponding to a Cartesian point.

atanh(Complex) - Static method in class com.imsl.math.Complex

Returns the inverse hyperbolic tangent (arc tanh) of a Complex, with branch cuts outside the interval [-1,1] on the real axis.

atanh(double) - Static method in class com.imsl.math.Hyperbolic

Returns the inverse hyperbolic tangent of its argument.

B

BACKWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression

Indicates backward regression.

BARTLETTS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation

Indicates standard error computation using Bartlett's formula.

BARTLETTS_FORMULA - Static variable in class com.imsl.stat.CrossCorrelation

Indicates standard error computation using Bartlett's formula.

BARTLETTS_FORMULA_NOCC - Static variable in class com.imsl.stat.CrossCorrelation

Indicates standard error computation using Bartlett's formula with the assumption of no cross-correlation.

BAR_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode

Flag to indicate a horizontal bar chart.

BAR_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode

Flag to indicate a vertical bar chart.

BEFORE_STEP - Static variable in class com.imsl.math.OdeRungeKutta

Used by method examineStep to indicate examining before the next step

BEGIN_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.

BEGIN_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for beginning a column label row is to be returned.

BEGIN_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatted string for beginning an entry is to be returned.

BEGIN_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for beginning a matrix is to be returned.

BEGIN_ROW - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for beginning a row is to be returned.

BEGIN_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for beginning a row label is to be returned.

BLUE - Static variable in interface com.imsl.chart.Colormap

Linear blue colormap.

BLUE_GREEN_RED_YELLOW - Static variable in interface com.imsl.chart.Colormap

Blue/green/red/yellow colormap.

BLUE_RED - Static variable in interface com.imsl.chart.Colormap

Blue/red colormap.

BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap

Blue/white colormap.

BOUNDED_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter

Flag to indicate bounded scaling.

BOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter

Flag to indicate bounded z-score scaling using the mean and standard deviation.

BOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter

Flag to indicate bounded z-score scaling using the median and mean absolute difference.

BOXPLOT_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.BoxPlot

Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.

BOXPLOT_TYPE_VERTICAL - Static variable in class com.imsl.chart.BoxPlot

Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.

BSpline - class com.imsl.math.BSpline.

BSpline represents and evaluates univariate B-splines.

BSpline() - Constructor for class com.imsl.math.BSpline

BW_LINEAR - Static variable in interface com.imsl.chart.Colormap

Black and white (grayscale) colormap.

Background - class com.imsl.chart.Background.

The background of a chart.

Bar - class com.imsl.chart.Bar.

A bar chart.

Bar(AxisXY) - Constructor for class com.imsl.chart.Bar

Constructs a bar chart.

Bar(AxisXY, double[]) - Constructor for class com.imsl.chart.Bar

Constructs a simple bar chart using supplied y data.

Bar(AxisXY, double[], double[]) - Constructor for class com.imsl.chart.Bar

Constructs a simple bar chart using supplied x and y data.

Bar(AxisXY, double[][]) - Constructor for class com.imsl.chart.Bar

Constructs a grouped bar chart using supplied x and y data.

Bar(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.Bar

Constructs a grouped bar chart using supplied x and y data.

Bar(AxisXY, double[][][]) - Constructor for class com.imsl.chart.Bar

Constructs a stacked, grouped bar chart using supplied y data.

Bar(AxisXY, double[], double[][][]) - Constructor for class com.imsl.chart.Bar

Constructs a stacked, grouped bar chart using supplied x and y data.

BarItem - class com.imsl.chart.BarItem.

A single bar in a bar chart.

BarSet - class com.imsl.chart.BarSet.

A set of bars in a bar chart.

Basis30e360 - Static variable in class com.imsl.finance.DayCountBasis

Computations based on the assumption of 30 days per month and 360 days per year.

BasisActual360 - Static variable in class com.imsl.finance.DayCountBasis

Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 360 days per year.

BasisActual365 - Static variable in class com.imsl.finance.DayCountBasis

Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 365 days per year.

BasisActualActual - Static variable in class com.imsl.finance.DayCountBasis

Computations are based on the actual calendar.

BasisNASD - Static variable in class com.imsl.finance.DayCountBasis

Computations based on the assumption of 30 days per month and 360 days per year.

BasisPart - interface com.imsl.finance.BasisPart.

Component of DayCountBasis.

BasisPart30E360 - Static variable in class com.imsl.finance.DayCountBasis

Computations based on the assumption of 30 days per month and 360 days per year.

BasisPart365 - Static variable in class com.imsl.finance.DayCountBasis

Computations based on the assumption of 365 days per year.

BasisPartActual - Static variable in class com.imsl.finance.DayCountBasis

Computations are based on the actual calendar.

BasisPartNASD - Static variable in class com.imsl.finance.DayCountBasis

Computations based on the assumption of 30 days per month and 360 days per year.

Bessel - class com.imsl.math.Bessel.

Collection of Bessel functions.

Bond - class com.imsl.finance.Bond.

Collection of bond functions.

Bond() - Constructor for class com.imsl.finance.Bond

BoundedLeastSquares - class com.imsl.math.BoundedLeastSquares.

Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.

BoundedLeastSquares(BoundedLeastSquares.Function, int, int, int, double[], double[]) - Constructor for class com.imsl.math.BoundedLeastSquares

Constructor for BoundedLeastSquares.

BoundedLeastSquares.FalseConvergenceException - exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException.

False convergence - The iterates appear to be converging to a noncritical point.

BoundedLeastSquares.FalseConvergenceException(String) - Constructor for class com.imsl.math.BoundedLeastSquares.FalseConvergenceException

Constructs an FalseConvergenceException with the specified detail message.

BoundedLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for class com.imsl.math.BoundedLeastSquares.FalseConvergenceException

Constructs an FalseConvergenceException with the specified detail message.

BoundedLeastSquares.Function - interface com.imsl.math.BoundedLeastSquares.Function.

Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.

BoundedLeastSquares.Jacobian - interface com.imsl.math.BoundedLeastSquares.Jacobian.

Public interface for the user-supplied function to compute the Jacobian.

BoxPlot - class com.imsl.chart.BoxPlot.

Draws a multiple-group Box plot.

BoxPlot(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.BoxPlot

Constructs a box plot chart node with specified x values.

BoxPlot(AxisXY, double[], BoxPlot.Statistics[]) - Constructor for class com.imsl.chart.BoxPlot

Constructs a box plot chart node with specified x values.

BoxPlot(AxisXY, double[][]) - Constructor for class com.imsl.chart.BoxPlot

Constructs a box plot chart.

BoxPlot.Statistics - class com.imsl.chart.BoxPlot.Statistics.

Computes the statistics for one set of observations in a Boxplot.

BoxPlot.Statistics(double[]) - Constructor for class com.imsl.chart.BoxPlot.Statistics

Creates a new instance of BoxPlot.Statistics.

BsInterpolate - class com.imsl.math.BsInterpolate.

Extension of the BSpline class to interpolate data points.

BsInterpolate(double[], double[]) - Constructor for class com.imsl.math.BsInterpolate

Constructs a B-spline that interpolates the given data points.

BsInterpolate(double[], double[], int) - Constructor for class com.imsl.math.BsInterpolate

Constructs a B-spline that interpolates the given data points and order, using a default "not-a-knot" spline knot sequence.

BsInterpolate(double[], double[], int, double[]) - Constructor for class com.imsl.math.BsInterpolate

Constructs a B-spline that interpolates the given data points, using the specified order and knots.

BsLeastSquares - class com.imsl.math.BsLeastSquares.

Extension of the BSpline class to compute a least squares spline approximation to data points.

BsLeastSquares(double[], double[], int) - Constructor for class com.imsl.math.BsLeastSquares

Constructs a least squares B-spline approximation to the given data points.

BsLeastSquares(double[], double[], int, int) - Constructor for class com.imsl.math.BsLeastSquares

Constructs a least squares B-spline approximation to the given data points.

BsLeastSquares(double[], double[], int, int, double[], double[]) - Constructor for class com.imsl.math.BsLeastSquares

Constructs a least squares B-spline approximation to the given data points.

backward(Complex[]) - Method in class com.imsl.math.ComplexFFT

Compute the complex periodic sequence from its Fourier coefficients.

backward(double[]) - Method in class com.imsl.math.FFT

Compute the real periodic sequence from its Fourier coefficients.

basis(int, double) - Method in interface com.imsl.stat.RegressionBasis

Public interface for the nonlinear least-squares function.

beforeFirst() - Method in class com.imsl.io.AbstractFlatFile

Moves the cursor to the front of this ResultSet object, just before the first row.

beginGet() - Method in class com.imsl.io.AbstractFlatFile

This method should be called at the start of every getType method.

beta(double, double) - Static method in class com.imsl.math.Sfun

Returns the value of the Beta function.

beta(double, double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the beta probability distribution function.

betaIncomplete(double, double, double) - Static method in class com.imsl.math.Sfun

Returns the incomplete Beta function ratio.

binomial(int, int, double) - Static method in class com.imsl.stat.Cdf

Evaluates the binomial distribution function.

binomialProb(int, int, double) - Static method in class com.imsl.stat.Cdf

Evaluates the binomial probability function.

breakPoint - Variable in class com.imsl.math.Spline

The breakpoint array of length n, where n is the number of piecewise polynomials.

byteValue() - Method in class com.imsl.math.Complex

Returns the value of the real part as a byte.

C

COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatted string for a given column label is to be returned.

CORRECTED_SSCP_MATRIX - Static variable in class com.imsl.stat.Covariances

Indicates corrected sums of squares and crossproducts matrix.

CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances

Indicates correlation matrix.

CORRELATION_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis

Indicates correlation matrix.

CURRENT - Static variable in class com.imsl.math.Physical

Candlestick - class com.imsl.chart.Candlestick.

Candlestick plot of stock data.

Candlestick(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick

Constructs a candlestick chart node beginning with specified start date.

Candlestick(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick

Constructs a candlestick chart node at specified axis points.

CandlestickItem - class com.imsl.chart.CandlestickItem.

A candlestick for the up days or the down days.

CategoricalGenLinModel - class com.imsl.stat.CategoricalGenLinModel.

Analyzes categorical data using logistic, probit, Poisson, and other linear models.

CategoricalGenLinModel(double[][], int) - Constructor for class com.imsl.stat.CategoricalGenLinModel

Constructs a new CategoricalGenLinModel.

CategoricalGenLinModel.ClassificationVariableException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException.

The ClassificationVariable vector has not been initialized.

CategoricalGenLinModel.ClassificationVariableException() - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException

Constructs a ClassificationVariableException.

CategoricalGenLinModel.ClassificationVariableLimitException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException.

The Classification Variable limit set by the user through setUpperBound has been exceeded.

CategoricalGenLinModel.ClassificationVariableLimitException(int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException

Constructs a ClassificationVariableLimitException.

CategoricalGenLinModel.ClassificationVariableValueException - exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException.

The number of distinct values for each Classification Variable must be greater than 1.

CategoricalGenLinModel.ClassificationVariableValueException(int, int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException

Constructs a ClassificationVariableValueException.

CategoricalGenLinModel.DeleteObservationsException - exception com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException.

The number of observations to be deleted (set by setObservationMax) has grown too large.

CategoricalGenLinModel.DeleteObservationsException(int) - Constructor for class com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException

Constructs a DeleteObservationsException.

Cdf - class com.imsl.stat.Cdf.

Cumulative distribution functions.

CdfFunction - interface com.imsl.stat.CdfFunction.

Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.

Chart - class com.imsl.chart.Chart.

The root node of the chart tree.

Chart() - Constructor for class com.imsl.chart.Chart

This is the root of our tree, it has no parent.

Chart(Component) - Constructor for class com.imsl.chart.Chart

This is the root of our tree, it has no parent.

Chart(Image) - Constructor for class com.imsl.chart.Chart

This is the root of our tree, it has no parent.

ChartFunction - interface com.imsl.chart.ChartFunction.

An interface that allows a function to be plotted.

ChartNode - class com.imsl.chart.ChartNode.

The base class of all of the nodes in the chart tree.

ChartNode(ChartNode) - Constructor for class com.imsl.chart.ChartNode

Construct a ChartNode object.

ChartServlet - class com.imsl.chart.ChartServlet.

The base class for chart servlets.

ChartServlet() - Constructor for class com.imsl.chart.ChartServlet

ChartSpline - class com.imsl.chart.ChartSpline.

Wrap a spline into a ChartFunction to be plotted.

ChartSpline(Spline) - Constructor for class com.imsl.chart.ChartSpline

Creates a ChartSpline from a Spline.

ChartSpline(Spline, int) - Constructor for class com.imsl.chart.ChartSpline

Creates a ChartSpline from the derivative of a Spline.

ChartTitle - class com.imsl.chart.ChartTitle.

The main title of a chart.

ChartXML - class com.imsl.chart.xml.ChartXML.

Create a Chart from an XML file.

ChartXML(String) - Constructor for class com.imsl.chart.xml.ChartXML

Creates a ChartXML from an XML file.

ChartXML(String, boolean) - Constructor for class com.imsl.chart.xml.ChartXML

Creates a ChartXML from an XML file.

ChartXML(InputSource, boolean) - Constructor for class com.imsl.chart.xml.ChartXML

Creates a ChartXML from an XML source.

ChartXML(Document) - Constructor for class com.imsl.chart.xml.ChartXML

Creates a ChartXML from a DOM tree.

CheckMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Deprecated. Check that all of the rows in the Complex matrix have the same length.

CheckMatrix(double[][]) - Static method in class com.imsl.math.Matrix

Deprecated. Check that all of the rows in the matrix have the same length.

CheckSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Deprecated. Check that the Complex matrix is square.

CheckSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix

Deprecated. Check that the matrix is square.

ChiSquaredTest - class com.imsl.stat.ChiSquaredTest.

Chi-squared goodness-of-fit test.

ChiSquaredTest(CdfFunction, double[], int) - Constructor for class com.imsl.stat.ChiSquaredTest

Constructor for the Chi-squared goodness-of-fit test.

ChiSquaredTest(CdfFunction, int, int) - Constructor for class com.imsl.stat.ChiSquaredTest

Constructor for the Chi-squared goodness-of-fit test

ChiSquaredTest(int) - Method in class com.imsl.stat.NormalityTest

Performs the chi-squared goodness-of-fit test.

ChiSquaredTest.DidNotConvergeException - exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException.

The iteration did not converge

ChiSquaredTest.DidNotConvergeException(String) - Constructor for class com.imsl.stat.ChiSquaredTest.DidNotConvergeException

ChiSquaredTest.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.DidNotConvergeException

ChiSquaredTest.NoObservationsException - exception com.imsl.stat.ChiSquaredTest.NoObservationsException.

There are no observations.

ChiSquaredTest.NoObservationsException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.NoObservationsException

ChiSquaredTest.NotCDFException - exception com.imsl.stat.ChiSquaredTest.NotCDFException.

The function is not a Cumulative Distribution Function (CDF).

ChiSquaredTest.NotCDFException(String, Object[]) - Constructor for class com.imsl.stat.ChiSquaredTest.NotCDFException

Cholesky - class com.imsl.math.Cholesky.

Cholesky factorization of a matrix of type double.

Cholesky(double[][]) - Constructor for class com.imsl.math.Cholesky

Create the Cholesky factorization of a symmetric positive definite matrix of type double.

Cholesky.NotSPDException - exception com.imsl.math.Cholesky.NotSPDException.

The matrix is not symmetric, positive definite.

Cholesky.NotSPDException() - Constructor for class com.imsl.math.Cholesky.NotSPDException

ClusterHierarchical - class com.imsl.stat.ClusterHierarchical.

Performs a hierarchical cluster analysis from a distance matrix.

ClusterHierarchical(double[][], int, int) - Constructor for class com.imsl.stat.ClusterHierarchical

Constructor for ClusterHierarchical.

ClusterKMeans - class com.imsl.stat.ClusterKMeans.

Perform a K-means (centroid) cluster analysis.

ClusterKMeans(double[][], double[][]) - Constructor for class com.imsl.stat.ClusterKMeans

Constructor for ClusterKMeans.

ClusterKMeans.ClusterNoPointsException - exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException.

There is a cluster with no points

ClusterKMeans.ClusterNoPointsException(String) - Constructor for class com.imsl.stat.ClusterKMeans.ClusterNoPointsException

ClusterKMeans.ClusterNoPointsException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.ClusterNoPointsException

ClusterKMeans.NoConvergenceException - exception com.imsl.stat.ClusterKMeans.NoConvergenceException.

Convergence did not occur within the maximum number of iterations.

ClusterKMeans.NoConvergenceException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NoConvergenceException

ClusterKMeans.NoConvergenceException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NoConvergenceException

ClusterKMeans.NonnegativeFreqException - exception com.imsl.stat.ClusterKMeans.NonnegativeFreqException.

Frequencies must be nonnegative.

ClusterKMeans.NonnegativeFreqException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeFreqException

ClusterKMeans.NonnegativeFreqException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeFreqException

ClusterKMeans.NonnegativeWeightException - exception com.imsl.stat.ClusterKMeans.NonnegativeWeightException.

Weights must be nonnegative.

ClusterKMeans.NonnegativeWeightException(String) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeWeightException

ClusterKMeans.NonnegativeWeightException(String, Object[]) - Constructor for class com.imsl.stat.ClusterKMeans.NonnegativeWeightException

Colormap - interface com.imsl.chart.Colormap.

Colormaps are mappings from the unit interval to Colors.

Complex - class com.imsl.math.Complex.

Set of mathematical functions for complex numbers.

Complex(Complex) - Constructor for class com.imsl.math.Complex

Constructs a Complex equal to the argument.

Complex(double, double) - Constructor for class com.imsl.math.Complex

Constructs a Complex with real and imaginary parts given by the input arguments.

Complex(double) - Constructor for class com.imsl.math.Complex

Constructs a Complex with a zero imaginary part.

Complex() - Constructor for class com.imsl.math.Complex

Constructs a Complex equal to zero.

ComplexFFT - class com.imsl.math.ComplexFFT.

Complex FFT.

ComplexFFT(int) - Constructor for class com.imsl.math.ComplexFFT

Constructs a complex FFT object.

ComplexLU - class com.imsl.math.ComplexLU.

LU factorization of a matrix of type Complex.

ComplexLU(Complex[][]) - Constructor for class com.imsl.math.ComplexLU

Creates the LU factorization of a square matrix of type Complex.

ComplexMatrix - class com.imsl.math.ComplexMatrix.

Complex matrix manipulation functions.

ContingencyTable - class com.imsl.stat.ContingencyTable.

Performs a chi-squared analysis of a two-way contingency table.

ContingencyTable(double[][]) - Constructor for class com.imsl.stat.ContingencyTable

Constructs and performs a chi-squared analysis of a two-way contingency table.

Contour - class com.imsl.chart.Contour.

A Contour chart shows level curves of a two-dimensional function.

Contour(AxisXY, double[], double[], double[][], double[]) - Constructor for class com.imsl.chart.Contour

Create a Contour chart from rectangularly gridded data.

Contour(AxisXY, double[], double[], double[][]) - Constructor for class com.imsl.chart.Contour

Create a Contour chart from rectangularly gridded data with computed contour levels.

Contour(AxisXY, double[], double[], double[]) - Constructor for class com.imsl.chart.Contour

Create a Contour chart from scattered data with computed contour levels.

Contour(AxisXY, double[], double[], double[], double[], int) - Constructor for class com.imsl.chart.Contour

Create a Contour chart from scattered data.

Contour.Legend - class com.imsl.chart.Contour.Legend.

A legend for a contour chart.

ContourLevel - class com.imsl.chart.ContourLevel.

ContourLevel draws a level curve line and the fill area between the level curve and the next smaller level curve.

Covariances - class com.imsl.stat.Covariances.

Computes the sample variance-covariance or correlation matrix.

Covariances(double[][]) - Constructor for class com.imsl.stat.Covariances

Constructor for Covariances.

Covariances.DiffObsDeletedException - exception com.imsl.stat.Covariances.DiffObsDeletedException.

Different observations are being deleted from return matrix than were originally entered.

Covariances.DiffObsDeletedException(String) - Constructor for class com.imsl.stat.Covariances.DiffObsDeletedException

Covariances.DiffObsDeletedException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.DiffObsDeletedException

Covariances.MoreObsDelThanEnteredException - exception com.imsl.stat.Covariances.MoreObsDelThanEnteredException.

More observations are being deleted from the output covariance matrix than were originally entered (the corresponding row, column of the incidence matrix is less than zero).

Covariances.MoreObsDelThanEnteredException(String) - Constructor for class com.imsl.stat.Covariances.MoreObsDelThanEnteredException

Covariances.MoreObsDelThanEnteredException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.MoreObsDelThanEnteredException

Covariances.NonnegativeFreqException - exception com.imsl.stat.Covariances.NonnegativeFreqException.

Frequencies must be nonnegative.

Covariances.NonnegativeFreqException(String) - Constructor for class com.imsl.stat.Covariances.NonnegativeFreqException

Covariances.NonnegativeFreqException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.NonnegativeFreqException

Covariances.NonnegativeWeightException - exception com.imsl.stat.Covariances.NonnegativeWeightException.

Weights must be nonnegative.

Covariances.NonnegativeWeightException(String) - Constructor for class com.imsl.stat.Covariances.NonnegativeWeightException

Covariances.NonnegativeWeightException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.NonnegativeWeightException

Covariances.TooManyObsDeletedException - exception com.imsl.stat.Covariances.TooManyObsDeletedException.

More observations have been deleted than were originally entered (the sum of frequencies has become negative).

Covariances.TooManyObsDeletedException(String) - Constructor for class com.imsl.stat.Covariances.TooManyObsDeletedException

Covariances.TooManyObsDeletedException(String, Object[]) - Constructor for class com.imsl.stat.Covariances.TooManyObsDeletedException

CrossCorrelation - class com.imsl.stat.CrossCorrelation.

Computes the sample cross-correlation function of two stationary time series.

CrossCorrelation(double[], double[], int) - Constructor for class com.imsl.stat.CrossCorrelation

Constructor to compute the sample cross-correlation function of two stationary time series.

CrossCorrelation.NonPosVariancesException - exception com.imsl.stat.CrossCorrelation.NonPosVariancesException.

The problem is ill-conditioned.

CrossCorrelation.NonPosVariancesException(String) - Constructor for class com.imsl.stat.CrossCorrelation.NonPosVariancesException

CrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for class com.imsl.stat.CrossCorrelation.NonPosVariancesException

CsAkima - class com.imsl.math.CsAkima.

Extension of the Spline class to handle the Akima cubic spline.

CsAkima(double[], double[]) - Constructor for class com.imsl.math.CsAkima

Constructs the Akima cubic spline interpolant to the given data points.

CsInterpolate - class com.imsl.math.CsInterpolate.

Extension of the Spline class to interpolate data points.

CsInterpolate(double[], double[]) - Constructor for class com.imsl.math.CsInterpolate

Constructs a cubic spline that interpolates the given data points.

CsInterpolate(double[], double[], int, double, int, double) - Constructor for class com.imsl.math.CsInterpolate

Constructs a cubic spline that interpolates the given data points with specified derivative endpoint conditions.

CsPeriodic - class com.imsl.math.CsPeriodic.

Extension of the Spline class to interpolate data points with periodic boundary conditions.

CsPeriodic(double[], double[]) - Constructor for class com.imsl.math.CsPeriodic

Constructs a cubic spline that interpolates the given data points with periodic boundary conditions.

CsShape - class com.imsl.math.CsShape.

Extension of the Spline class to interpolate data points consistent with the concavity of the data.

CsShape(double[], double[]) - Constructor for class com.imsl.math.CsShape

Construct a cubic spline interpolant which is consistent with the concavity of the data.

CsShape.TooManyIterationsException - exception com.imsl.math.CsShape.TooManyIterationsException.

Too many iterations.

CsShape.TooManyIterationsException() - Constructor for class com.imsl.math.CsShape.TooManyIterationsException

CsShape.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.CsShape.TooManyIterationsException

CsShape.TooManyIterationsException(Object[]) - Constructor for class com.imsl.math.CsShape.TooManyIterationsException

CsSmooth - class com.imsl.math.CsSmooth.

Extension of the Spline class to construct a smooth cubic spline from noisy data points.

CsSmooth(double[], double[]) - Constructor for class com.imsl.math.CsSmooth

Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.

CsSmooth(double[], double[], double[]) - Constructor for class com.imsl.math.CsSmooth

Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.

CsSmoothC2 - class com.imsl.math.CsSmoothC2.

Extension of the Spline class used to construct a spline for noisy data points using an alternate method.

CsSmoothC2(double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2

Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967).

CsSmoothC2(double[], double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2

Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967) with weights supplied by the user.

cancelRowUpdates() - Method in class com.imsl.io.AbstractFlatFile

Cancels the updates made to the current row in this ResultSet object.

cdf(double) - Method in interface com.imsl.stat.CdfFunction

Public interface for the user-supplied cumulative distribution function to be used by InverseCdf.

ceil(double) - Static method in class com.imsl.math.JMath

Returns the value of a double rounded toward positive infinity to an integral value.

chart - Variable in class com.imsl.chart.JPanelChart

The embedded chart.

check(int) - Static method in class com.imsl.Messages

check(int) - Method in class com.imsl.chart.Draw

checkCompatibility(Physical, Physical) - Static method in class com.imsl.math.Physical

Checks the compatibility of two Physical objects.

checkMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Check that all of the rows in the Complex matrix have the same length.

checkMatrix(double[][]) - Static method in class com.imsl.math.Matrix

Check that all of the rows in the matrix have the same length.

checkSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Check that the Complex matrix is square.

checkSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix

Check that the matrix is square.

checkerboard(int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a checkerboard pattern.

chi(double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the chi-squared distribution function.

circle(int, int, int) - Method in class com.imsl.chart.DrawMap

Sets a circle as the target.

clearWarnings() - Method in class com.imsl.io.AbstractFlatFile

Clears all warnings reported on this ResultSet object.

clone() - Method in class com.imsl.chart.Chart

Returns a clone of the graphics tree.

clone(Hashtable) - Method in class com.imsl.chart.Chart

Returns a clone of this node.

clone(Hashtable) - Method in class com.imsl.chart.ChartNode

Returns a deep-copy clone of this node.

clone(Object, Hashtable) - Method in class com.imsl.chart.ChartNode

Returns a deep copy of an Object.

clone(Hashtable, Hashtable) - Method in class com.imsl.chart.ChartNode

Returns a deep copy of a Hashtable.

clone(Vector, Hashtable) - Method in class com.imsl.chart.ChartNode

Returns a deep copy of a vector of ChartNode's.

clone() - Method in class com.imsl.math.LinearProgramming

Creates and returns a copy of this object.

clone() - Method in class com.imsl.stat.FaureSequence

Returns a copy of this object.

close() - Method in class com.imsl.io.AbstractFlatFile

Releases this ResultSet object's database and JDBC resources immediately instead of waiting for this to happen when it is automatically closed.

coef - Variable in class com.imsl.math.BSpline

The B-spline coefficient array.

coef - Variable in class com.imsl.math.Spline

Coefficients of the piecewise polynomials.

color(double) - Method in interface com.imsl.chart.Colormap

Maps the parameterization interval [0,1] into Colors.

com.imsl - package com.imsl

com.imsl.chart - package com.imsl.chart

com.imsl.chart.xml - package com.imsl.chart.xml

com.imsl.datamining.neural - package com.imsl.datamining.neural

com.imsl.finance - package com.imsl.finance

com.imsl.io - package com.imsl.io

com.imsl.math - package com.imsl.math

com.imsl.stat - package com.imsl.stat

compareTo(Object) - Method in class com.imsl.math.Complex

Compares this Complex to another Object.

compareTo(Complex) - Method in class com.imsl.math.Complex

Compares two Complex objects.

compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Function

Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.

compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Jacobian

Public interface for the user-supplied function to compute the Jacobian.

compute() - Method in class com.imsl.stat.ANOVAFactorial

Analyzes a balanced factorial design with fixed effects.

compute() - Method in class com.imsl.stat.ARMA

Computes least-square estimates of parameters for an ARMA model.

compute() - Method in class com.imsl.stat.ClusterKMeans

Computes the cluster means.

compute(int) - Method in class com.imsl.stat.Covariances

Computes the matrix.

compute(double[], int[]) - Method in class com.imsl.stat.Difference

Computes a Difference series.

compute() - Method in class com.imsl.stat.GARCH

Computes estimates of the parameters of a GARCH(p,q) model.

compute() - Method in class com.imsl.stat.MultipleComparisons

Performs Student-Newman-Keuls multiple comparisons test.

compute(double[][], double[]) - Method in class com.imsl.stat.SelectionRegression

Computes the best multiple linear regression models.

compute(double[][], double[], double[]) - Method in class com.imsl.stat.SelectionRegression

Computes the best weighted multiple linear regression models.

compute(double[][], double[], double[], double[]) - Method in class com.imsl.stat.SelectionRegression

Computes the best weighted multiple linear regression models using frequencies for each observation.

compute(double[][], int) - Method in class com.imsl.stat.SelectionRegression

Computes the best multiple linear regression models using a user-supplied covariance matrix.

compute() - Method in class com.imsl.stat.SignTest

Performs a sign test.

compute() - Method in class com.imsl.stat.StepwiseRegression

Builds the multiple linear regression models using forward selection, backward selection, or stepwise selection.

compute() - Method in class com.imsl.stat.WilcoxonRankSum

Performs a Wilcoxon rank sum test.

computeLags(int[], int[], double[]) - Method in class com.imsl.datamining.neural.TimeSeriesClassFilter

Computes lags of an array sorted first by class designations and then descending chronological order.

computeLags(int, double[][]) - Method in class com.imsl.datamining.neural.TimeSeriesFilter

Lags time series data to a format used for input to a neural network.

computeMin(MinUncon.Function) - Method in class com.imsl.math.MinUncon

Return the minimum of a smooth function of a single variable of type double using function values only or using function values and derivatives.

computeMin(MinUnconMultiVar.Function) - Method in class com.imsl.math.MinUnconMultiVar

Return the minimum point of a function of n variables of type double using a finite-difference gradient or using a user-supplied gradient.

computeRoots(double[]) - Method in class com.imsl.math.ZeroPolynomial

Computes the roots of the polynomial with real coefficients.

computeRoots(Complex[]) - Method in class com.imsl.math.ZeroPolynomial

Computes the roots of the polynomial with Complex coefficients.

computeStatistics(double[][], double[][]) - Method in class com.imsl.datamining.neural.Network

Computes error statistics.

computeZeros(ZeroFunction.Function, double[]) - Method in class com.imsl.math.ZeroFunction

Returns the zeros of a univariate function.

condition(Complex[][]) - Method in class com.imsl.math.ComplexLU

Return an estimate of the reciprocal of the L1 condition number.

condition(double[][]) - Method in class com.imsl.math.LU

Return an estimate of the reciprocal of the L1 condition number of a matrix.

confidenceMean(double) - Method in class com.imsl.stat.Summary

Returns the confidence interval for the mean (assuming normality).

confidenceVariance(double) - Method in class com.imsl.stat.Summary

Returns the confidence interval for the variance (assuming normality).

conjugate(Complex) - Static method in class com.imsl.math.Complex

Returns the complex conjugate of a Complex object.

constant(String) - Static method in class com.imsl.math.Physical

Returns the value of a constant, given its name.

constant(String, String) - Static method in class com.imsl.math.Physical

Returns the value of a constant, given its name, in the specified units.

convert(Physical, String) - Static method in class com.imsl.math.Physical

Converts a value to a different set of units.

convexity(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the convexity for a security.

copy() - Method in class com.imsl.chart.Chart

Copy the chart to the clipboard.

copyAndSortData(double[], double[]) - Method in class com.imsl.math.Spline

Copy and sort xData into breakPoint and yData into the first column of coef.

copyAndSortData(double[], double[], double[]) - Method in class com.imsl.math.Spline

Copy and sort xData into breakPoint and yData into the first column of coef.

copysign(double, double) - Static method in class com.imsl.math.IEEE

Returns a value with the magnitude of x and with the sign bit of y.

cos(Complex) - Static method in class com.imsl.math.Complex

Returns the cosine of a Complex.

cos(double) - Static method in class com.imsl.math.JMath

Returns the cosine of a double.

cosh(Complex) - Static method in class com.imsl.math.Complex

Returns the hyperbolic cosh of a Complex.

cosh(double) - Static method in class com.imsl.math.Hyperbolic

Returns the hyperbolic cosine of its argument.

cot(double) - Static method in class com.imsl.math.Sfun

Returns the cotangent of a double.

countTokens() - Method in class com.imsl.io.Tokenizer

Returns the number of times that the nextToken method can be called without generating an exception.

coupdaybs(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the number of days starting with the beginning of the coupon period and ending with the settlement date.

coupdays(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the number of days in the coupon period containing the settlement date.

coupdaysnc(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the number of days starting with the settlement date and ending with the next coupon date.

coupncd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the first coupon date which follows the settlement date.

coupnum(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the number of coupons payable between the settlement date and the maturity date.

couppcd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the coupon date which immediately precedes the settlement date.

createHiddenLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Creates a HiddenLayer.

createHiddenLayer() - Method in class com.imsl.datamining.neural.Network

Creates the next HiddenLayer in the Network.

createInput() - Method in class com.imsl.datamining.neural.InputLayer

Creates an InputNode in the InputLayer of the neural network.

createInputs(int) - Method in class com.imsl.datamining.neural.InputLayer

Creates a number of InputNodes in this Layer of the neural network.

createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer

Creates a Perceptron in this Layer with a specified activation function and bias.

createPerceptron() - Method in class com.imsl.datamining.neural.HiddenLayer

Creates a Perceptron in this Layer of the neural network.

createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer

Creates a Perceptron in this Layer with a specified Activation and bias.

createPerceptron() - Method in class com.imsl.datamining.neural.OutputLayer

Creates a Perceptron in this Layer of the neural network.

createPerceptrons(int) - Method in class com.imsl.datamining.neural.HiddenLayer

Creates a number of Perceptrons in this Layer of the neural network.

createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer

Creates a number of Perceptrons in this Layer with the specified bias.

createPerceptrons(int) - Method in class com.imsl.datamining.neural.OutputLayer

Creates a number of Perceptrons in this Layer of the neural network.

createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer

Creates a number of Perceptrons in this Layer with specified activation and bias.

crosshatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a horizonal and vertical crosshatch pattern.

cumipmt(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance

Returns the cumulative interest paid between two periods.

cumprinc(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance

Returns the cumulative principal paid between two periods.

currentType - Variable in class com.imsl.chart.Draw

D

DASH_PATTERN_DASH - Static variable in class com.imsl.chart.ChartNode

Flag to draw a dashed line.

DASH_PATTERN_DASH_DOT - Static variable in class com.imsl.chart.ChartNode

Flag to draw a dash-dot pattern line.

DASH_PATTERN_DOT - Static variable in class com.imsl.chart.ChartNode

Flag to draw a dotted line.

DASH_PATTERN_SOLID - Static variable in class com.imsl.chart.ChartNode

Flag to draw solid line.

DATA_TYPE_ERROR_X - Static variable in class com.imsl.chart.ErrorBar

Value for attribute "DataType" indicating that this is a horizontal error bar.

DATA_TYPE_ERROR_Y - Static variable in class com.imsl.chart.ErrorBar

Value for attribute "DataType" indicating that this is a vertical error bar.

DATA_TYPE_FILL - Static variable in class com.imsl.chart.ChartNode

Value for attribute "DataType" indicating that the area between the lines connecting the data points and the horizontal reference line (y = attribute "Reference") should be filled.

DATA_TYPE_LINE - Static variable in class com.imsl.chart.ChartNode

Value for attribute "DataType" indicating that the data points should be connected with line segments.

DATA_TYPE_MARKER - Static variable in class com.imsl.chart.ChartNode

Value for attribute "DataType" indicating that a marker should be drawn at each data point.

DATA_TYPE_PICTURE - Static variable in class com.imsl.chart.ChartNode

Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.

DAY - Static variable in class com.imsl.chart.HighLowClose

Milliseconds per day

Data - class com.imsl.chart.Data.

Draws a data node.

Data(ChartNode) - Constructor for class com.imsl.chart.Data

Creates a data node.

Data(ChartNode, double[]) - Constructor for class com.imsl.chart.Data

Creates a data node with y values.

Data(ChartNode, ChartFunction, double, double) - Constructor for class com.imsl.chart.Data

Creates a data node with y values.

Data(ChartNode, double[], double[]) - Constructor for class com.imsl.chart.Data

Creates a data node with x and y values.

DayCountBasis - class com.imsl.finance.DayCountBasis.

The Day Count Basis.

DayCountBasis(BasisPart, BasisPart) - Constructor for class com.imsl.finance.DayCountBasis

Creates a new DayCountBasis.

Difference - class com.imsl.stat.Difference.

Differences a seasonal or nonseasonal time series.

Difference() - Constructor for class com.imsl.stat.Difference

Constructor for Difference.

DiscriminantAnalysis - class com.imsl.stat.DiscriminantAnalysis.

Performs a linear or a quadratic discriminant function analysis among several known groups and the use of either reclassification, split sample, or the leaving-out-one methods in order to evaluate the rule.

DiscriminantAnalysis(int, int) - Constructor for class com.imsl.stat.DiscriminantAnalysis

Constructor for DiscriminantAnalysis.

DiscriminantAnalysis.CovarianceSingularException - exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException.

The variance-Covariance matrix is singular.

DiscriminantAnalysis.CovarianceSingularException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException

DiscriminantAnalysis.CovarianceSingularException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException

DiscriminantAnalysis.EmptyGroupException - exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException.

There are no observations in a group.

DiscriminantAnalysis.EmptyGroupException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.EmptyGroupException

DiscriminantAnalysis.EmptyGroupException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.EmptyGroupException

DiscriminantAnalysis.SumOfWeightsNegException - exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException.

The sum of the weights have become negative.

DiscriminantAnalysis.SumOfWeightsNegException(String) - Constructor for class com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException

DiscriminantAnalysis.SumOfWeightsNegException(String, Object[]) - Constructor for class com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException

Dissimilarities - class com.imsl.stat.Dissimilarities.

Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.

Dissimilarities(double[][], int, int, int) - Constructor for class com.imsl.stat.Dissimilarities

Constructor for Dissimilarities.

Dissimilarities(double[][], int, int, int, int[]) - Constructor for class com.imsl.stat.Dissimilarities

Constructor for Dissimilarities.

Dissimilarities.NoPositiveVarianceException - exception com.imsl.stat.Dissimilarities.NoPositiveVarianceException.

No variable has positive variance.

Dissimilarities.NoPositiveVarianceException() - Constructor for class com.imsl.stat.Dissimilarities.NoPositiveVarianceException

Constructs a NoPositiveVarianceException.

Dissimilarities.ScaleFactorZeroException - exception com.imsl.stat.Dissimilarities.ScaleFactorZeroException.

The computations cannot continue because a scale factor is zero.

Dissimilarities.ScaleFactorZeroException(int) - Constructor for class com.imsl.stat.Dissimilarities.ScaleFactorZeroException

Constructs a ScaleFactorZeroException.

Dissimilarities.ZeroNormException - exception com.imsl.stat.Dissimilarities.ZeroNormException.

The computations cannot continue because the Euclidean norm of the column is equal to zero.

Dissimilarities.ZeroNormException(int) - Constructor for class com.imsl.stat.Dissimilarities.ZeroNormException

Constructs a ZeroNormException.

Draw - class com.imsl.chart.Draw.

Chart tree renderer.

Draw(Graphics, Dimension) - Constructor for class com.imsl.chart.Draw

Contructs a Draw object.

DrawMap - class com.imsl.chart.DrawMap.

Creates an HTML client-side imagemap from a chart tree.

DrawMap(Graphics, Dimension) - Constructor for class com.imsl.chart.DrawMap

Contructs a DrawMap object.

DrawPick - class com.imsl.chart.DrawPick.

The DrawPick class.

DrawPick(MouseEvent, Graphics, Dimension) - Constructor for class com.imsl.chart.DrawPick

Contructs a DrawPick object.

dataRange(double[]) - Method in class com.imsl.chart.Bar

Overrides Data.dataRange.

dataRange(double[]) - Method in class com.imsl.chart.BarItem

Overides Data.dataRange.

dataRange(double[]) - Method in class com.imsl.chart.BarSet

dataRange(double[]) - Method in class com.imsl.chart.BoxPlot

Overrides Data.dataRange.

dataRange(double[]) - Method in class com.imsl.chart.Contour

Update the data range.

dataRange(double[]) - Method in class com.imsl.chart.Data

Update the data range.

dataRange(double[]) - Method in class com.imsl.chart.ErrorBar

Overrides Data.dataRange.

dataRange(double[]) - Method in class com.imsl.chart.Heatmap

Update the data range.

dataRange(double[]) - Method in class com.imsl.chart.HighLowClose

Overrides Data.dataRange.

daysBetween(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart

Returns the number of days from date1 to date2.

daysInPeriod(GregorianCalendar, int) - Method in interface com.imsl.finance.BasisPart

Returns the number of days in a coupon period.

db(double, double, int, int, int) - Static method in class com.imsl.finance.Finance

Returns the depreciation of an asset using the fixed-declining balance method.

ddb(double, double, int, int, double) - Static method in class com.imsl.finance.Finance

Returns the depreciation of an asset using the double-declining balance method.

decode(double) - Method in class com.imsl.datamining.neural.ScaleFilter

Unscales a value.

decode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter

Unscales an array of values.

decode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter

Unscales a single column of a two dimensional array of values.

decode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter

Decodes a binary encoded array into its nominal category.

decode(int[][]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter

Decodes a matrix representing the binary encoded columns of the nominal variable.

decode(double) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Decodes an encoded ordinal variable.

decode(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Decodes an array of encoded ordinal values.

defineConstant(String, Physical) - Static method in class com.imsl.math.Physical

Defines a new constant.

definePrefix(String, double) - Static method in class com.imsl.math.Physical

Defines a new prefix.

defineUnit(String, Physical) - Static method in class com.imsl.math.Physical

Defines a new unit.

deleteRow() - Method in class com.imsl.io.AbstractFlatFile

Deletes the current row from this ResultSet object and from the underlying database.

derivative(double, double) - Method in interface com.imsl.datamining.neural.Activation

Returns the value of the derivative of the activation function.

derivative(double) - Method in class com.imsl.math.BSpline

Returns the value of the first derivative of the B-spline at a point.

derivative(double, int) - Method in class com.imsl.math.BSpline

Returns the value of the derivative of the B-spline at a point.

derivative(double[], int) - Method in class com.imsl.math.BSpline

Returns the value of the derivative of the B-spline at each point of an array.

derivative(double) - Method in class com.imsl.math.Spline

Returns the value of the first derivative of the spline at a point.

derivative(double, int) - Method in class com.imsl.math.Spline

Returns the value of the derivative of the spline at a point.

derivative(double[], int) - Method in class com.imsl.math.Spline

Returns the value of the derivative of the spline at each point of an array.

derivative(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Derivative

Computes the weight, frequency, and partial derivatives of the residual given the parameter vector theta for a single observation.

descending(double[], int[]) - Static method in class com.imsl.stat.Sort

Sort an array into descending order.

descending(double[]) - Static method in class com.imsl.stat.Sort

Sort an array into descending order.

descending(double[][], int) - Static method in class com.imsl.stat.Sort

Function to sort a matrix into descending order by specified keys.

descending(double[][], int[]) - Static method in class com.imsl.stat.Sort

Function to sort a matrix into descending order by specified keys.

descending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort

Function to sort an array into descending order by specified keys.

descending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort

Function to sort a matrix into descending order by specified keys.

determinant() - Method in class com.imsl.math.ComplexLU

Return the determinant of the matrix used to construct this instance.

determinant() - Method in class com.imsl.math.LU

Return the determinant of the matrix used to construct this instance.

diagonal(int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a diagonal pattern.

diamond(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a diamond pattern (a checkerboard rotated 45 degrees).

diamondHatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a crosshatch on a 45 degree angle.

dim - Variable in class com.imsl.math.Physical

disc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the implied interest rate of a discount bond.

divide(Complex, Complex) - Static method in class com.imsl.math.Complex

Returns the result of a Complex object divided by a Complex object, x/y.

divide(Complex, double) - Static method in class com.imsl.math.Complex

Returns the result of a Complex object divided by a double, x/y.

divide(double, Complex) - Static method in class com.imsl.math.Complex

Returns the result of a double divided by a Complex object, x/y.

divide(Physical, Physical) - Static method in class com.imsl.math.Physical

Divide two Physical objects.

divide(Physical, double) - Static method in class com.imsl.math.Physical

Divide a Physical object by a double.

divide(double, Physical) - Static method in class com.imsl.math.Physical

Divide a double by a Physical object.

doGet(HttpServletRequest, HttpServletResponse) - Method in class com.imsl.chart.ChartServlet

Returns the chart as a PNG image.

doGetBytes(int) - Method in class com.imsl.io.AbstractFlatFile

Implements the actual getBytes().

doGetBytes(int) - Method in class com.imsl.io.FlatFile

Gets the value of the designated column in the current row as a byte array.

doNext() - Method in class com.imsl.io.AbstractFlatFile

Implements the operations on the file required by the method next().

doNext() - Method in class com.imsl.io.FlatFile

Moves the cursor down one row from its current position.

dollarde(double, int) - Static method in class com.imsl.finance.Finance

Converts a fractional price to a decimal price.

dollarfr(double, int) - Static method in class com.imsl.finance.Finance

Converts a decimal price to a fractional price.

dot(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a pattern that is an array of circles.

doubleValue() - Method in class com.imsl.math.Complex

Returns the value of the real part as a double.

doubleValue() - Method in class com.imsl.math.Physical

Returns the value of this dimensionless object.

downdate(double[]) - Method in class com.imsl.math.Cholesky

Downdates the factorization by subtracting a rank-1 matrix.

downdateX(double[]) - Method in class com.imsl.stat.NormTwoSample

Removes the observations in x from the first sample.

downdateY(double[]) - Method in class com.imsl.stat.NormTwoSample

Removes the observations in y from the second sample.

drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw

Draws the outline of a circular or elliptical arc covering the specified rectangle.

drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap

Draws the outline of a circular or elliptical arc covering the specified rectangle.

drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick

Draw an arc.

drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.Draw

Draw an error bar.

drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawMap

Draw an error bar.

drawErrorBar(int, int, int, int) - Method in class com.imsl.chart.DrawPick

Draw ErrorBar

drawImage(Image, int, int) - Method in class com.imsl.chart.Draw

Draw an image.

drawImage(Image, int, int) - Method in class com.imsl.chart.DrawMap

Draw Image

drawImage(Image, int, int) - Method in class com.imsl.chart.DrawPick

Draw Image

drawLine(int, int, int, int) - Method in class com.imsl.chart.Draw

Draw a line from (x0,y0) to (x1,y1).

drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawMap

Draw a line from (x0,y0) to (x1,y1).

drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawPick

Draw a line from (x0,y0) to (x1,y1).

drawMarker(int, int) - Method in class com.imsl.chart.Draw

Draw a marker.

drawMarker(int, int) - Method in class com.imsl.chart.DrawMap

Draw a marker.

drawMarker(int, int) - Method in class com.imsl.chart.DrawPick

Draw a marker.

drawRotatedText(Text, int, int, float) - Method in class com.imsl.chart.Draw

Draws a text object, at the specified angle, with its lower left point being at (x,y).

drawText(Text, int, int) - Method in class com.imsl.chart.Draw

Draws a text object.

drawText(Text, int, int, boolean) - Method in class com.imsl.chart.Draw

Draws a text object.

drawText(Graphics, Text) - Method in class com.imsl.chart.Draw

Draws the text.

drawText(Text, int, int, boolean) - Method in class com.imsl.chart.DrawMap

drawText(Text, int, int) - Method in class com.imsl.chart.DrawPick

duration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the Macauley's duration of a security where the security has periodic interest payments.

E

E - Static variable in class com.imsl.math.JMath

END_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.

END_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a column label row is to be returned.

END_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatted string for ending an entry is to be returned.

END_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a matrix is to be returned.

END_ROW - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a row is to be returned.

END_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatting string for ending a row label is to be returned.

ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat

This flag as the type argument to format, indicates that the formatted string for a given entry is to be returned.

EPSILON_LARGE - Static variable in class com.imsl.math.Sfun

The largest relative spacing for doubles.

EPSILON_LARGE - Static variable in class com.imsl.math.Spline

The largest relative spacing for double.

EPSILON_SMALL - Static variable in class com.imsl.math.QuadraticProgramming

The smallest relative spacing for doubles.

EPSILON_SMALL - Static variable in class com.imsl.math.Sfun

The smallest relative spacing for doubles.

EPSILON_SMALL - Static variable in class com.imsl.math.ZeroPolynomial

The smallest relative spacing for doubles.

ERROR_BAR - Static variable in class com.imsl.chart.Draw

Eigen - class com.imsl.math.Eigen.

Collection of Eigen System functions.

Eigen(double[][]) - Constructor for class com.imsl.math.Eigen

Constructs the eigenvalues and the eigenvectors of a real square matrix.

Eigen(double[][], boolean) - Constructor for class com.imsl.math.Eigen

Constructs the eigenvalues and (optionally) the eigenvectors of a real square matrix.

Eigen.DidNotConvergeException - exception com.imsl.math.Eigen.DidNotConvergeException.

The iteration did not converge

Eigen.DidNotConvergeException(String) - Constructor for class com.imsl.math.Eigen.DidNotConvergeException

Eigen.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.math.Eigen.DidNotConvergeException

EpochTrainer - class com.imsl.datamining.neural.EpochTrainer.

Two-stage training using randomly selected training patterns in stage I.

EpochTrainer(Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer

Creates a single stage EpochTrainer.

EpochTrainer(Trainer, Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer

Creates an two-stage EpochTrainer.

EpsilonAlgorithm - class com.imsl.math.EpsilonAlgorithm.

The class is used to determine the limit of a sequence of approximations, by means of the Epsilon algorithm of P.

EpsilonAlgorithm() - Constructor for class com.imsl.math.EpsilonAlgorithm

Initializes an EpsilonAlgorithm with a maximum table size of 50.

EpsilonAlgorithm(int) - Constructor for class com.imsl.math.EpsilonAlgorithm

Initializes an EpsilonAlgorithm.

ErrorBar - class com.imsl.chart.ErrorBar.

Data points with error bars.

ErrorBar(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.ErrorBar

Creates a set of error bars centered at (x[k],y[k]) and with extents low[k],high[k].

effect(double, int) - Static method in class com.imsl.finance.Finance

Returns the effective annual interest rate.

encode(double) - Method in class com.imsl.datamining.neural.ScaleFilter

Scales a value.

encode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter

Scales an array of values.

encode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter

Scales a single column of a two dimensional array of values.

encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter

Encodes class data prior to its use in neural network training.

encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter

Apply forward encoding to a value.

encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Encodes an array of ordinal categories into an array of transformed percentages.

encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Encodes an ordinal category.

endErrorBar() - Method in class com.imsl.chart.Draw

Stop drawing an error bar.

endErrorBar() - Method in class com.imsl.chart.DrawMap

endErrorBar() - Method in class com.imsl.chart.DrawPick

End ErrorBar

endFill() - Method in class com.imsl.chart.Draw

Stop drawing a filled region.

endFill() - Method in class com.imsl.chart.DrawMap

endFill() - Method in class com.imsl.chart.DrawPick

End fill

endImage() - Method in class com.imsl.chart.Draw

Stop drawing an image.

endImage() - Method in class com.imsl.chart.DrawMap

endImage() - Method in class com.imsl.chart.DrawPick

End Image

endLine() - Method in class com.imsl.chart.Draw

Finish drawing lines.

endLine() - Method in class com.imsl.chart.DrawMap

endLine() - Method in class com.imsl.chart.DrawPick

Finish drawing lines.

endMarker() - Method in class com.imsl.chart.Draw

Finish drawing markers.

endMarker() - Method in class com.imsl.chart.DrawMap

endMarker() - Method in class com.imsl.chart.DrawPick

Finish drawing markers.

endText() - Method in class com.imsl.chart.Draw

Stop drawing text.

endText() - Method in class com.imsl.chart.DrawMap

endText() - Method in class com.imsl.chart.DrawPick

End Text

equals(Complex) - Method in class com.imsl.math.Complex

Compares with another Complex.

equals(Object) - Method in class com.imsl.math.Complex

Compares this object against the specified object.

erf(double) - Static method in class com.imsl.math.Sfun

Returns the error function of a double.

erfInverse(double) - Static method in class com.imsl.math.Sfun

Returns the inverse of the error function.

erfc(double) - Static method in class com.imsl.math.Sfun

Returns the complementary error function of a double.

erfcInverse(double) - Static method in class com.imsl.math.Sfun

Returns the inverse of the complementary error function.

error(String, Object[]) - Method in class com.imsl.chart.xml.ChartXML

Handles error messages.

error(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML

Receive notification of a recoverable error.

error(double, double) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error

Returns the contribution to the error from a single training output target.

errorGradient(double, double) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error

Returns the derivative of the error function with respect to the forecast output.

eval(HyperRectangleQuadrature.Function) - Method in class com.imsl.math.HyperRectangleQuadrature

Returns the value of the integral over the unit cube.

eval(HyperRectangleQuadrature.Function, double[], double[]) - Method in class com.imsl.math.HyperRectangleQuadrature

Returns the value of the integral over a cube.

eval(Quadrature.Function, double, double) - Method in class com.imsl.math.Quadrature

Returns the value of the integral from a to b.

eval(double, double) - Method in class com.imsl.stat.InverseCdf

Evaluates the inverse CDF function.

examineStep(int, double, double[]) - Method in class com.imsl.math.OdeRungeKutta

Called before and after each internal step.

excludeFirst(boolean) - Method in class com.imsl.stat.Difference

If set to true, the observations lost due to differencing will be excluded.

exp(Complex) - Static method in class com.imsl.math.Complex

Returns the exponential of a Complex z, exp(z).

exp(double) - Static method in class com.imsl.math.JMath

Returns the exponential of a double.

expectedNormalOrderStatistic(int, int) - Static method in class com.imsl.stat.Ranks

Returns the expected value of a normal order statistic.

expm1(double) - Static method in class com.imsl.math.Hyperbolic

Returns exp(x)-1, the exponential of x minus 1.

extrapolate(double) - Method in class com.imsl.math.EpsilonAlgorithm

Extrapolates the convergence limit of a sequence.

F

F(double, double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the F distribution function.

FFT - class com.imsl.math.FFT.

FFT functions.

FFT(int) - Constructor for class com.imsl.math.FFT

Constructs an FFT object.

FILL - Static variable in class com.imsl.chart.Draw

FILL_TYPE_GRADIENT - Static variable in class com.imsl.chart.ChartNode

Value for attribute "FillType" indicating that the region is to be drawn in a color gradient as specified by the attribute Gradient.

FILL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode

Value for attribute "FillType" and "FillOutlineType" indicating that the region is not to be drawn.

FILL_TYPE_PAINT - Static variable in class com.imsl.chart.ChartNode

Value for attribute "FillType" indicating that the region is to be drawn using the texture specified by the attribute FillPaint.

FILL_TYPE_SOLID - Static variable in class com.imsl.chart.ChartNode

Value for attribute "FillType" and "FillOutlineType" indicating that the region is to be drawn using the solid color specified by the attribute FillColor or FillOutlineColor.

FIRST_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate

FORWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression

Indicates forward regression.

FULL - Static variable in class com.imsl.math.PrintMatrix

This flag as the argument to setMatrixType, indicates that the full matrix is to be printed.

FactorAnalysis - class com.imsl.stat.FactorAnalysis.

Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.

FactorAnalysis(double[][], int, int) - Constructor for class com.imsl.stat.FactorAnalysis

Constructor for FactorAnalysis.

FactorAnalysis.BadVarianceException - exception com.imsl.stat.FactorAnalysis.BadVarianceException.

Bad variance error.

FactorAnalysis.BadVarianceException(String) - Constructor for class com.imsl.stat.FactorAnalysis.BadVarianceException

FactorAnalysis.BadVarianceException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.BadVarianceException

FactorAnalysis.EigenvalueException - exception com.imsl.stat.FactorAnalysis.EigenvalueException.

Eigenvalue error.

FactorAnalysis.EigenvalueException(String) - Constructor for class com.imsl.stat.FactorAnalysis.EigenvalueException

FactorAnalysis.EigenvalueException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.EigenvalueException

FactorAnalysis.NoDegreesOfFreedomException - exception com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException.

No degrees of freedom error.

FactorAnalysis.NoDegreesOfFreedomException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException

FactorAnalysis.NoDegreesOfFreedomException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException

FactorAnalysis.NonPositiveEigenvalueException - exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException.

Non positive eigenvalue error.

FactorAnalysis.NonPositiveEigenvalueException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException

FactorAnalysis.NonPositiveEigenvalueException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException

FactorAnalysis.NotPositiveDefiniteException - exception com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException.

Covariance matrix not positive definite.

FactorAnalysis.NotPositiveDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException

FactorAnalysis.NotPositiveDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException

FactorAnalysis.NotPositiveSemiDefiniteException - exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException.

Covariance matrix not positive semi-definite.

FactorAnalysis.NotPositiveSemiDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException

FactorAnalysis.NotPositiveSemiDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException

FactorAnalysis.NotSemiDefiniteException - exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException.

Hessian matrix not semi-definite.

FactorAnalysis.NotSemiDefiniteException(String) - Constructor for class com.imsl.stat.FactorAnalysis.NotSemiDefiniteException

FactorAnalysis.NotSemiDefiniteException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.NotSemiDefiniteException

FactorAnalysis.RankException - exception com.imsl.stat.FactorAnalysis.RankException.

Rank of covariance matrix error.

FactorAnalysis.RankException(String) - Constructor for class com.imsl.stat.FactorAnalysis.RankException

FactorAnalysis.RankException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.RankException

FactorAnalysis.SingularException - exception com.imsl.stat.FactorAnalysis.SingularException.

Covariance matrix singular error.

FactorAnalysis.SingularException(String) - Constructor for class com.imsl.stat.FactorAnalysis.SingularException

FactorAnalysis.SingularException(String, Object[]) - Constructor for class com.imsl.stat.FactorAnalysis.SingularException

FaureSequence - class com.imsl.stat.FaureSequence.

Generates the low-discrepancy Faure sequence.

FaureSequence(int) - Constructor for class com.imsl.stat.FaureSequence

Creates a Faure sequence with the default base.

FaureSequence(int, int, int) - Constructor for class com.imsl.stat.FaureSequence

Creates a Faure sequence.

FeedForwardNetwork - class com.imsl.datamining.neural.FeedForwardNetwork.

A representation of a feed forward neural network.

FeedForwardNetwork() - Constructor for class com.imsl.datamining.neural.FeedForwardNetwork

Creates a new instance of FeedForwardNetwork.

FillPaint - class com.imsl.chart.FillPaint.

A collection of methods to create Paint objects for fill areas.

Finance - class com.imsl.finance.Finance.

Collection of finance functions.

FlatFile - class com.imsl.io.FlatFile.

Reads a text file as a ResultSet.

FlatFile(BufferedReader, Tokenizer) - Constructor for class com.imsl.io.FlatFile

Creates a FlatFile from a BufferedReader.

FlatFile(BufferedReader) - Constructor for class com.imsl.io.FlatFile

Creates a FlatFile with the CSV tokenizer.

FlatFile(String) - Constructor for class com.imsl.io.FlatFile

Creates a FlatFile from a CSV file.

FlatFile(String, Tokenizer) - Constructor for class com.imsl.io.FlatFile

Creates a FlatFile from a file with the default tokenizer.

FlatFile.Parser - interface com.imsl.io.FlatFile.Parser.

Defines a method that parses a String into an Object.

f(double) - Method in interface com.imsl.chart.ChartFunction

Function to be charted.

f(double) - Method in class com.imsl.chart.ChartSpline

Function to be charted.

f(double[]) - Method in interface com.imsl.math.HyperRectangleQuadrature.Function

Returns the value of the function at the given point.

f(double[]) - Method in interface com.imsl.math.MinConGenLin.Function

Public interface for the function to be minimized.

f(double[], int, boolean[]) - Method in interface com.imsl.math.MinConNLP.Function

Compute the value of the function at the given point.

f(double) - Method in interface com.imsl.math.MinUncon.Function

Public interface for the smooth function of a single variable to be minimized.

f(double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Function

Public interface for the multivariate function to be minimized.

f(double[], double[]) - Method in interface com.imsl.math.NonlinLeastSquares.Function

Public interface for the nonlinear least-squares function.

f(double, double[], double[]) - Method in interface com.imsl.math.OdeRungeKutta.Function

Returns the value of the function at the given point.

f(double) - Method in interface com.imsl.math.Quadrature.Function

Returns the value of the function at the given point.

f(double) - Method in interface com.imsl.math.RadialBasis.Function

A radial basis function.

f(double) - Method in class com.imsl.math.RadialBasis.Gaussian

f(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric

f(double) - Method in interface com.imsl.math.ZeroFunction.Function

Returns the value of the function at the given point.

f(double[], double[]) - Method in interface com.imsl.math.ZeroSystem.Function

Returns the value of the function at the given point.

f(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Function

Computes the weight, frequency, and residual given the parameter vector theta for a single observation.

fact(int) - Static method in class com.imsl.math.Sfun

Returns the factorial of an integer.

factor - Variable in class com.imsl.math.ComplexLU

LU factorization of A with partial pivoting

factor - Variable in class com.imsl.math.LU

LU factorization of A with partial pivoting

fatalError(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML

Receive notification of a non-recoverable error.

fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw

Fills a circular or elliptical arc covering the specified rectangle.

fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap

Fills a circular or elliptical arc covering the specified rectangle.

fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick

Fills a circular or elliptical arc covering the specified rectangle.

fillColor - Variable in class com.imsl.chart.Draw

fillOutlineColor - Variable in class com.imsl.chart.Draw

fillOutlineType - Variable in class com.imsl.chart.Draw

fillPaint - Variable in class com.imsl.chart.Draw

fillPolygon(int[], int[], int) - Method in class com.imsl.chart.Draw

Fill a polygon.

fillPolygon(Polygon) - Method in class com.imsl.chart.Draw

Fill a polygon defined by a Polygon object.

fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawMap

Fill a polygon.

fillPolygon(Polygon) - Method in class com.imsl.chart.DrawMap

Fill a polygon defined by a Polygon object.

fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawPick

Fill a polygon.

fillPolygon(Polygon) - Method in class com.imsl.chart.DrawPick

Fill a polygon defined by a Polygon object.

fillRectangle(int, int, int, int) - Method in class com.imsl.chart.Draw

Fill a rectangle.

fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawMap

Fill a rectangle.

fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawPick

Fill a rectangle.

fillType - Variable in class com.imsl.chart.Draw

filter() - Method in class com.imsl.stat.KalmanFilter

Performs Kalman filtering and evaluates the likelihood function for the state-space model.

finalize() - Method in class com.imsl.chart.Chart

findColumn(String) - Method in class com.imsl.io.AbstractFlatFile

Maps the given ResultSet column name to its ResultSet column index.

findColumnName(int) - Method in class com.imsl.io.AbstractFlatFile

Maps the given columnIndex into its column name.

findLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the Link between two Nodes.

findLinks(Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns all of the Links to a given Node.

finite(double) - Static method in class com.imsl.math.IEEE

Finite number test on an argument of type double.

fire() - Method in class com.imsl.chart.DrawPick

Fires the pickListeners for all of the picked nodes.

firePickListeners(MouseEvent) - Method in class com.imsl.chart.ChartNode

Fires the pick listeners defined at this node and at all of its ancestors, if the event "hits" the node.

first() - Method in class com.imsl.io.AbstractFlatFile

Moves the cursor to the first row in this ResultSet object.

floatValue() - Method in class com.imsl.math.Complex

Returns the value of the real part as a float.

floatValue() - Method in class com.imsl.math.Physical

Returns the value of this dimensionless object.

floor(double) - Static method in class com.imsl.math.JMath

Returns the value of a double rounded toward negative infinity to an integral value.

forecast(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Computes a forecast using the Network.

forecast(double[]) - Method in class com.imsl.datamining.neural.Network

Returns a forecast for each of the Network's outputs computed from the trained Network.

forecast(int) - Method in class com.imsl.stat.ARMA

Computes forecasts and their associated probability limits for an ARMA model.

format(LogRecord) - Method in class com.imsl.math.MinConNLP.Formatter

format(int, Object, int, int, ParsePosition) - Method in class com.imsl.math.PrintMatrixFormat

Returns a formatted string.

formatLabel(double, double) - Method in class com.imsl.chart.Data

formatMessage(String, String, Object[]) - Static method in class com.imsl.Messages

A message is formatted using a MessageFormat string retrieved from the named resource bundle using the given key.

formatMessage(String, String) - Static method in class com.imsl.Messages

A message is formatted, without arguments, using a MessageFormat string retrieved from the named resource bundle using the given key.

forward(Complex[]) - Method in class com.imsl.math.ComplexFFT

Compute the Fourier coefficients of a complex periodic sequence.

forward(double[]) - Method in class com.imsl.math.FFT

Compute the Fourier coefficients of a real periodic sequence.

frobeniusNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Return the Frobenius norm of a Complex matrix.

frobeniusNorm(double[][]) - Static method in class com.imsl.math.Matrix

Return the Frobenius norm of a matrix.

fv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance

Returns the future value of an investment.

fvschedule(double, double[]) - Static method in class com.imsl.finance.Finance

Returns the future value of an initial principal taking into consideration a schedule of compound interest rates.

G

GARCH - class com.imsl.stat.GARCH.

Computes estimates of the parameters of a GARCH(p,q) model.

GARCH(int, int, double[], double[]) - Constructor for class com.imsl.stat.GARCH

Constructor for GARCH.

GARCH.ConstrInconsistentException - exception com.imsl.stat.GARCH.ConstrInconsistentException.

The equality constraints are inconsistent.

GARCH.ConstrInconsistentException(String) - Constructor for class com.imsl.stat.GARCH.ConstrInconsistentException

GARCH.ConstrInconsistentException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.ConstrInconsistentException

GARCH.EqConstrInconsistentException - exception com.imsl.stat.GARCH.EqConstrInconsistentException.

The equality constraints and the bounds on the variables are found to be inconsistent.

GARCH.EqConstrInconsistentException(String) - Constructor for class com.imsl.stat.GARCH.EqConstrInconsistentException

GARCH.EqConstrInconsistentException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.EqConstrInconsistentException

GARCH.NoVectorXException - exception com.imsl.stat.GARCH.NoVectorXException.

No vector X satisfies all of the constraints.

GARCH.NoVectorXException(String) - Constructor for class com.imsl.stat.GARCH.NoVectorXException

GARCH.NoVectorXException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.NoVectorXException

GARCH.TooManyIterationsException - exception com.imsl.stat.GARCH.TooManyIterationsException.

Number of function evaluations exceeded 1000.

GARCH.TooManyIterationsException(String) - Constructor for class com.imsl.stat.GARCH.TooManyIterationsException

GARCH.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.TooManyIterationsException

GARCH.VarsDeterminedException - exception com.imsl.stat.GARCH.VarsDeterminedException.

The variables are determined by the equality constraints.

GARCH.VarsDeterminedException(String) - Constructor for class com.imsl.stat.GARCH.VarsDeterminedException

GARCH.VarsDeterminedException(String, Object[]) - Constructor for class com.imsl.stat.GARCH.VarsDeterminedException

GENERALIZED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis

Indicates generalized least squares method.

GREEN - Static variable in interface com.imsl.chart.Colormap

Linear green colormap.

GREEN_PINK - Static variable in interface com.imsl.chart.Colormap

Green/pink colormap.

GREEN_RED_BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap

Green/red/blue/white colormap.

GREEN_WHITE_EXPONENTIAL - Static variable in interface com.imsl.chart.Colormap

Exponential green/white colormap.

GREEN_WHITE_LINEAR - Static variable in interface com.imsl.chart.Colormap

Linear green/white colormap.

Grid - class com.imsl.chart.Grid.

Draws the grid lines perpendicular to an axis.

GridPolar - class com.imsl.chart.GridPolar.

Draws the grid lines for a polar plot.

g(double) - Method in interface com.imsl.datamining.neural.Activation

Returns the value of the activation function.

g(double) - Method in interface com.imsl.math.MinUncon.Derivative

Public interface for the smooth function of a single variable to be minimized.

g(double) - Method in interface com.imsl.math.RadialBasis.Function

The derivative of the radial basis function.

g(double) - Method in class com.imsl.math.RadialBasis.Gaussian

g(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric

gamma(double) - Static method in class com.imsl.math.Sfun

Returns the Gamma function of a double.

gamma(double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the gamma distribution function.

get(String) - Method in class com.imsl.chart.xml.ChartXML

Returns a generated object given the id attribute in the XML tag that created the object.

getALT() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ALT" attribute.

getALT() - Method in class com.imsl.chart.DrawMap

Returns the current ALT string.

getANOVA() - Method in class com.imsl.math.RadialBasis

Returns the ANOVA statistics from the linear regression.

getANOVA() - Method in class com.imsl.stat.LinearRegression

Get an analysis of variance table and related statistics.

getANOVA() - Method in class com.imsl.stat.StepwiseRegression

Get an analysis of variance table and related statistics.

getANOVA() - Method in class com.imsl.stat.UserBasisRegression

Get an analysis of variance table and related statistics.

getANOVATable() - Method in class com.imsl.stat.ANOVAFactorial

Returns the analysis of variance table.

getAR() - Method in class com.imsl.stat.ARMA

Returns the final autoregressive parameter estimates.

getAR() - Method in class com.imsl.stat.GARCH

Returns the estimated values of autoregressive (AR) parameters.

getActivation() - Method in class com.imsl.datamining.neural.Perceptron

Returns the activation function.

getAdjustedRSquared() - Method in class com.imsl.stat.ANOVA

Returns the adjusted R-squared (in percent).

getAkaike() - Method in class com.imsl.stat.GARCH

Returns the value of Akaike Information Criterion evaluated at the estimated parameter array.

getAlignment() - Method in class com.imsl.chart.Text

Gets the alignment for this Text object.

getArray(int) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.

getArray(String) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.

getArray() - Method in class com.imsl.stat.ANOVA

Returns the ANOVA values as an array.

getAsciiStream(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.

getAsciiStream(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.

getAttribute(String) - Method in class com.imsl.chart.ChartNode

Gets an attribute.

getAutoCorrelationX() - Method in class com.imsl.stat.CrossCorrelation

Returns the autocorrelations of the time series x.

getAutoCorrelationY() - Method in class com.imsl.stat.CrossCorrelation

Returns the autocorrelations of the time series y.

getAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation

Returns the autocorrelations of the time series x.

getAutoCovariance() - Method in class com.imsl.stat.ARMA

Returns the autocovariances of the time series z.

getAutoCovarianceX() - Method in class com.imsl.stat.CrossCorrelation

Returns the autocovariances of the time series x.

getAutoCovarianceY() - Method in class com.imsl.stat.CrossCorrelation

Returns the autocovariances of the time series y.

getAutoCovariances() - Method in class com.imsl.stat.AutoCorrelation

Returns the variance and autocovariances of the time series x.

getAutoscaleInput() - Method in class com.imsl.chart.ChartNode

Returns the value of the "AutoscaleInput" attribute.

getAutoscaleMinimumTimeInterval() - Method in class com.imsl.chart.ChartNode

Returns the value of the "AutoscaleMinimumTimeInterval" attribute.

getAutoscaleOutput() - Method in class com.imsl.chart.ChartNode

Returns the value of the "AutoscaleOutput" attribute.

getAxis() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Axis" attribute.

getAxisLabel() - Method in class com.imsl.chart.Axis1D

Returns the label node associated with this axis.

getAxisLine() - Method in class com.imsl.chart.Axis1D

Returns the axis line node associated with this axis.

getAxisR() - Method in class com.imsl.chart.Polar

Return the radius axis node.

getAxisRLabel() - Method in class com.imsl.chart.AxisR

Returns the AxisRLabel node.

getAxisRLine() - Method in class com.imsl.chart.AxisR

Returns the AxisRLine node.

getAxisRMajorTick() - Method in class com.imsl.chart.AxisR

Returns the major tick node associated with this axis.

getAxisTheta() - Method in class com.imsl.chart.Polar

Return the angular axis node.

getAxisTitle() - Method in class com.imsl.chart.Axis1D

Returns the title node associated with this axis.

getAxisUnit() - Method in class com.imsl.chart.Axis1D

Returns the unit node associated with this axis.

getAxisX() - Method in class com.imsl.chart.AxisXY

Return the x-axis node.

getAxisY() - Method in class com.imsl.chart.AxisXY

Return the y-axis node.

getBackground() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Background" attribute.

getBalancedTable() - Method in class com.imsl.stat.TableMultiWay

Returns an object containing the balanced table.

getBarData() - Method in class com.imsl.chart.Bar

Returns the "BarData" attribute.

getBarGap() - Method in class com.imsl.chart.ChartNode

Returns the value of the "BarGap" attribute.

getBarItem() - Method in class com.imsl.chart.BarSet

Returns an array of BarItems.

getBarItem(int) - Method in class com.imsl.chart.BarSet

Returns the BarItem given the index.

getBarSet() - Method in class com.imsl.chart.Bar

Returns the BarSet object.

getBarSet(int, int) - Method in class com.imsl.chart.Bar

Returns the BarSet object.

getBarSet(int) - Method in class com.imsl.chart.Bar

Returns the BarSet object.

getBarType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "BarType" attribute.

getBarWidth() - Method in class com.imsl.chart.ChartNode

Returns the value of the "BarWidth" attribute.

getBase() - Method in class com.imsl.stat.FaureSequence

Returns the base.

getBias() - Method in class com.imsl.datamining.neural.Perceptron

Returns the bias for this perceptron.

getBigDecimal(int, int) - Method in class com.imsl.io.AbstractFlatFile

Deprecated.

getBigDecimal(String, int) - Method in class com.imsl.io.AbstractFlatFile

Deprecated.

getBigDecimal(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.

getBigDecimal(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.

getBinaryStream(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a binary stream of uninterpreted bytes.

getBinaryStream(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a stream of uninterpreted bytes.

getBlob(int) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.

getBlob(String) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.

getBlomScores(double[]) - Method in class com.imsl.stat.Ranks

Gets the Blom version of normal scores for each observation.

getBodies() - Method in class com.imsl.chart.BoxPlot

Returns a node containing the body elements in the Box plot.

getBoolean(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.

getBoolean(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.

getBooleanAttribute(String, boolean) - Method in class com.imsl.chart.ChartNode

Convenience routine to get a Boolean-valued attribute.

getBounds() - Method in class com.imsl.datamining.neural.ScaleFilter

Retrieves bounds used during bounded scaling.

getBoxPlotType() - Method in class com.imsl.chart.BoxPlot

Returns the value of the "BoxPlotType" attribute.

getBreakpoints() - Method in class com.imsl.math.Spline

Returns a copy of the breakpoints.

getByte(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.

getByte(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.

getBytes(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.

getBytes(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.

getCaseAnalysis() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the case analysis.

getCellCounts() - Method in class com.imsl.stat.ChiSquaredTest

Returns the cell counts.

getCenter() - Method in class com.imsl.datamining.neural.ScaleFilter

Retrieves the measure of center to be used during z-score scaling.

getCharacterStream(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.

getCharacterStream(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.

getChart() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Chart" attribute.

getChart(HttpServletRequest) - Method in class com.imsl.chart.ChartServlet

Returns the chart found in the session saved with the key "chart"+id, where id is the value of the "id" parameter in the request.

getChart() - Method in class com.imsl.chart.JFrameChart

Return the Chart object.

getChart() - Method in class com.imsl.chart.JPanelChart

Return the Chart object.

getChart() - Method in class com.imsl.chart.xml.ChartXML

Returns the root node of the chart tree.

getChartServletName() - Method in class com.imsl.chart.JspBean

Returns the URL of the servlet used to render the chart.

getChartTitle() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ChartTitle" attribute.

getChiSquared() - Method in class com.imsl.stat.ChiSquaredTest

Returns the chi-squared statistic.

getChiSquared() - Method in class com.imsl.stat.ContingencyTable

Returns the Pearson chi-squared test statistic.

getChiSquared() - Method in class com.imsl.stat.NormalityTest

Returns the chi-square statistic for the chi-squared goodness-of-fit test.

getChiSquaredTest() - Method in class com.imsl.stat.NormOneSample

Returns the test statistic associated with the chi-squared test for variances.

getChiSquaredTest() - Method in class com.imsl.stat.NormTwoSample

Returns the test statistic associated with the chi-squared test for common, or pooled, variances.

getChiSquaredTestDF() - Method in class com.imsl.stat.NormOneSample

Returns the degrees of freedom associated with the chi-squared test for variances.

getChiSquaredTestDF() - Method in class com.imsl.stat.NormTwoSample

Returns the degrees of freedom associated with the chi-squared test for the common, or pooled, variances.

getChiSquaredTestP() - Method in class com.imsl.stat.NormOneSample

Returns the probability of a larger chi-squared associated with the chi-squared test for variances.

getChiSquaredTestP() - Method in class com.imsl.stat.NormTwoSample

Returns the probability of a larger chi-squared associated with the chi-squared test for common, or pooled, variances.

getChildren() - Method in class com.imsl.chart.ChartNode

Returns an array of the children of this node.

getClassMembership() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the group number to which the observation was classified.

getClassTable() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the classification table.

getClassificationVariableCounts() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the number of values taken by each classification variable.

getClassificationVariableValues() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the distinct values of the classification variables in ascending order.

getClipBounds() - Method in class com.imsl.chart.Draw

Get the clipping rectangle.

getClipData() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ClipData" attribute.

getClob(int) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.

getClob(String) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.

getClose() - Method in class com.imsl.chart.HighLowClose

Gets the value of the attribute "Close".

getClusterCounts() - Method in class com.imsl.stat.ClusterKMeans

Returns the number of observations in each cluster.

getClusterLeftSons() - Method in class com.imsl.stat.ClusterHierarchical

Returns the left sons of each merged cluster.

getClusterLevel() - Method in class com.imsl.stat.ClusterHierarchical

Returns the level at which the clusters are joined.

getClusterMembership(int) - Method in class com.imsl.stat.ClusterHierarchical

Returns the cluster membership of each observation.

getClusterMembership() - Method in class com.imsl.stat.ClusterKMeans

Returns the cluster membership for each observation.

getClusterRightSons() - Method in class com.imsl.stat.ClusterHierarchical

Returns the right sons of each merged cluster.

getClusterSSQ() - Method in class com.imsl.stat.ClusterKMeans

Returns the within sum of squares for each cluster.

getCoefficient(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests

Returns the estimate for a coefficient.

getCoefficient(int) - Method in class com.imsl.stat.NonlinearRegression

Returns the estimate for a coefficient.

getCoefficient(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests

Returns the estimate for a coefficient of the independent variable.

getCoefficientOfVariation() - Method in class com.imsl.stat.ANOVA

Returns the coefficient of variation (in percent).

getCoefficientStatistics(int) - Method in class com.imsl.stat.SelectionRegression.Statistics

Returns the coefficients statistics for each of the best regressions found for each subset considered.

getCoefficientTTests() - Method in class com.imsl.stat.LinearRegression

Returns statistics relating to the regression coefficients.

getCoefficientTTests() - Method in class com.imsl.stat.StepwiseRegression

Returns the student-t test statistics for the regression coefficients.

getCoefficientVIF() - Method in class com.imsl.stat.StepwiseRegression

Returns the variance inflation factors for the final model in this invocation.

getCoefficients() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the linear discriminant function coefficients.

getCoefficients() - Method in class com.imsl.stat.LinearRegression

Returns the regression coefficients.

getCoefficients() - Method in class com.imsl.stat.NonlinearRegression

Returns the regression coefficients.

getCoefficients() - Method in class com.imsl.stat.UserBasisRegression

Returns the regression coefficients.

getColorAttribute(String) - Method in class com.imsl.chart.ChartNode

Convenience routine to get a Color-valued attribute.

getColormap() - Method in class com.imsl.chart.Heatmap

Returns the value of the "Colormap" attribute.

getColumnClass(int) - Method in class com.imsl.io.AbstractFlatFile

Returns the class of the items in the specified column.

getColumnCount() - Method in class com.imsl.io.AbstractFlatFile

Returns the number of columns in this ResultSet object.

getColumnCount() - Method in class com.imsl.io.FlatFile

Returns the number of columns in this ResultSet object.

getComponent() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Component" attribute.

getConcatenatedViewport() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.

getConcurrency() - Method in class com.imsl.io.AbstractFlatFile

Returns the concurrency mode of this ResultSet object.

getConstant() - Method in class com.imsl.stat.ARMA

Returns the constant parameter estimate.

getConstraintResiduals() - Method in class com.imsl.math.MinConNLP

Returns the constraint residuals.

getContingencyCoef() - Method in class com.imsl.stat.ContingencyTable

Returns contingency coefficient.

getContourLegend() - Method in class com.imsl.chart.Contour

Returns the contour chart legend.

getContourLevel() - Method in class com.imsl.chart.Contour

Returns all of the contour levels.

getContourLevel(int) - Method in class com.imsl.chart.Contour

Returns a ContourLevel.

getContributions() - Method in class com.imsl.stat.ContingencyTable

Returns the contributions to chi-squared for each cell in the table.

getCorrelations() - Method in class com.imsl.stat.FactorAnalysis

Returns the correlations of the principal components.

getCount() - Method in class com.imsl.stat.FaureSequence

getCovB() - Method in class com.imsl.stat.KalmanFilter

Returns the mean squared error matrix for b divided by sigma squared.

getCovV() - Method in class com.imsl.stat.KalmanFilter

Returns the variance-covariance matrix of v divided by sigma squared.

getCovariance() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the array of covariances.

getCovarianceMatrix() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the estimated asymptotic covariance matrix of the coefficients.

getCovariancesSwept() - Method in class com.imsl.stat.StepwiseRegression

Returns the results after cov has been swept for the columns corresponding to the variables in the model.

getCramersV() - Method in class com.imsl.stat.ContingencyTable

Returns Cramer's V.

getCreateImageMap() - Method in class com.imsl.chart.JspBean

Returns true if a client-side imagemap is to be created.

getCriterionOption() - Method in class com.imsl.stat.SelectionRegression

Returns the criterion option used to calculate the regression estimates.

getCriterionValues(int) - Method in class com.imsl.stat.SelectionRegression.Statistics

Returns an array containing the values of the best criterion for the number of variables considered.

getCross() - Method in class com.imsl.chart.AxisXY

Returns the value of the "Cross" attribute.

getCrossCorrelation() - Method in class com.imsl.stat.CrossCorrelation

Returns the cross-correlations between the time series x and y.

getCrossCorrelation() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the cross-correlations between the channels of x and y.

getCrossCovariance() - Method in class com.imsl.stat.CrossCorrelation

Returns the cross-covariances between the time series x and y.

getCrossCovariance() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the cross-covariances between the channels of x and y.

getCursorName() - Method in class com.imsl.io.AbstractFlatFile

Gets the name of the SQL cursor used by this ResultSet object.

getCustomTransform() - Method in class com.imsl.chart.ChartNode

Returns the value of the "CustomTransform" attribute.

getCutpoints() - Method in class com.imsl.stat.ChiSquaredTest

Returns the cutpoints.

getDFError() - Method in class com.imsl.stat.NonlinearRegression

Returns the degrees of freedom for error.

getDataType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "DataType" attribute.

getDate(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.

getDate(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.

getDate(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.

getDate(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.

getDaysInYear(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart

Returns the number of days in the year.

getDegreesOfFreedom() - Method in class com.imsl.stat.ChiSquaredTest

Returns the degrees of freedom in chi-squared.

getDegreesOfFreedom() - Method in class com.imsl.stat.ContingencyTable

Returns the degrees of freedom for the chi-squared tests associated with the table.

getDegreesOfFreedom() - Method in class com.imsl.stat.NormalityTest

Returns the degrees of freedom for the chi-squared goodness-of-fit test.

getDegreesOfFreedomForError() - Method in class com.imsl.stat.ANOVA

Returns the degrees of freedom for error.

getDegreesOfFreedomForModel() - Method in class com.imsl.stat.ANOVA

Returns the degrees of freedom for model.

getDensity() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Density" attribute.

getDesignVariableMeans() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the means of the design variables.

getDeviations() - Method in class com.imsl.stat.ARMA

Returns the deviations from each forecast that give the confidence percent probability limits.

getDeviceMarkerSize() - Method in class com.imsl.chart.Draw

Returns the marker size in device corrdinates.

getDiffMean() - Method in class com.imsl.stat.NormTwoSample

Returns the difference in means, mean of x - mean of y.

getDimension() - Method in class com.imsl.stat.FaureSequence

Returns the dimension of the sequence.

getDimension() - Method in interface com.imsl.stat.RandomSequence

Returns the dimension of the sequence.

getDistanceMatrix() - Method in class com.imsl.stat.Dissimilarities

Returns the distance matrix.

getDouble(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.

getDouble(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.

getDoubleAttribute(String, double) - Method in class com.imsl.chart.ChartNode

Convenience routine to get a Double-valued attribute.

getDoubleBuffering() - Method in class com.imsl.chart.ChartNode

Returns the value of the "DoubleBuffering" attribute.

getDown() - Method in class com.imsl.chart.Candlestick

Returns the CandlestickItem for down days.

getDual() - Method in class com.imsl.math.QuadraticProgramming

Returns the dual (Lagrange multipliers).

getDualSolution() - Method in class com.imsl.math.LinearProgramming

Returns the dual solution.

getDunnSidak(int, int) - Method in class com.imsl.stat.ANOVA

Computes the confidence interval of i-th mean - j-th mean, using the Dunn-Sidak method.

getEnumValue(String) - Static method in class com.imsl.chart.xml.ChartXML

Returns the int corresponding to an enumeration.

getEpochSize() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the number of sample training patterns in each stage 1 epoch.

getError() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the function used to compute the error to be minimized.

getErrorEstimate() - Method in class com.imsl.math.EpsilonAlgorithm

Returns the current error estimate.

getErrorEstimate() - Method in class com.imsl.math.HyperRectangleQuadrature

Returns an estimate of the relative error in the computed result.

getErrorEstimate() - Method in class com.imsl.math.Quadrature

Returns an estimate of the relative error in the computed result.

getErrorGradient() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the value of the gradient of the error function with respect to the weights.

getErrorGradient() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer

Returns the value of the gradient of the error function with respect to the weights.

getErrorGradient() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the value of the gradient of the error function with respect to the weights.

getErrorGradient() - Method in interface com.imsl.datamining.neural.Trainer

Returns the value of the gradient of the error function with respect to the weights.

getErrorMeanSquare() - Method in class com.imsl.stat.ANOVA

Returns the error mean square.

getErrorNumber() - Method in class com.imsl.LicenseManagerException

Returns the FlexLM error number for this exception.

getErrorStatus() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the training error status.

getErrorStatus() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer

Returns the error status from the trainer.

getErrorStatus() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the error status from the trainer.

getErrorStatus() - Method in interface com.imsl.datamining.neural.Trainer

Returns the error status.

getErrorStatus() - Method in class com.imsl.math.MinUnconMultiVar

Returns the non-fatal error status.

getErrorStatus() - Method in class com.imsl.math.NonlinLeastSquares

Get information about the performance of NonlinLeastSquares.

getErrorStatus() - Method in class com.imsl.math.Quadrature

Returns the non-fatal error status.

getErrorStatus() - Method in class com.imsl.stat.NonlinearRegression

Gets information about the performance of NonlinearRegression.

getErrorValue() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the value of the error function.

getErrorValue() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer

Returns the final value of the error function.

getErrorValue() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the final value of the error function.

getErrorValue() - Method in interface com.imsl.datamining.neural.Trainer

Returns the value of the error function minimized by the trainer.

getExactMean() - Method in class com.imsl.stat.ContingencyTable

Returns exact mean.

getExactStdev() - Method in class com.imsl.stat.ContingencyTable

Returns exact standard deviation.

getExpectedCounts() - Method in class com.imsl.stat.ChiSquaredTest

Returns the expected counts.

getExpectedValues() - Method in class com.imsl.stat.ContingencyTable

Returns the expected values of each cell in the table.

getExplode() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Explode" attribute.

getExtendedLikelihoodObservations() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns a vector indicating which observations are included in the extended likelihood.

getF() - Method in class com.imsl.stat.ANOVA

Returns the F statistic.

getFTest() - Method in class com.imsl.stat.NormTwoSample

Returns the F test value of the F test for equality of variances.

getFTestDFdenominator() - Method in class com.imsl.stat.NormTwoSample

Returns the denominator degrees of freedom of the F test for equality of variances.

getFTestDFnumerator() - Method in class com.imsl.stat.NormTwoSample

Returns the numerator degrees of freedom of the F test for equality of variances.

getFTestP() - Method in class com.imsl.stat.NormTwoSample

Returns the probability of a larger F in absolute value for the F test for equality of variances, assuming equal variances.

getFactorLoadings() - Method in class com.imsl.stat.FactorAnalysis

Returns the unrotated factor loadings.

getFarMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the array of far markers.

getFarMarkers() - Method in class com.imsl.chart.BoxPlot

Returns the FarMarkers node.

getFeature() - Method in class com.imsl.LicenseManagerException

Returns the name of the feature that could not be licensed.

getFetchDirection() - Method in class com.imsl.io.AbstractFlatFile

Returns the fetch direction for this ResultSet object.

getFetchSize() - Method in class com.imsl.io.AbstractFlatFile

Returns the fetch size for this ResultSet object.

getFillColor() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FillColor" attribute.

getFillOutlineColor() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FillOutlineColor" attribute.

getFillOutlineType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FillOutlineType" attribute.

getFillPaint() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FillPaint" attribute.

getFillType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FillType" attribute.

getFinalActiveConstraints() - Method in class com.imsl.math.MinConGenLin

Returns the indices of the final active constraints.

getFinalActiveConstraintsNum() - Method in class com.imsl.math.MinConGenLin

Returns the final number of active constraints.

getFirstTick() - Method in class com.imsl.chart.Axis1D

Convenience routine to get the "FirstTick" attribute.

getFloat(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.

getFloat(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.

getFont() - Method in class com.imsl.chart.ChartNode

Convenience routine which gets a Font object based on the "FontName", "FontStyle" and "FontSize" attributes.

getFontName() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FontName" attribute.

getFontSize() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FontSize" attribute.

getFontStyle() - Method in class com.imsl.chart.ChartNode

Returns the value of the "FontStyle" attribute.

getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the gradient with respect to the weights.

getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.Network

Returns the first derivatives with respect to the weights evaluated at x.

getFormatter() - Static method in class com.imsl.datamining.neural.EpochTrainer

Returns the logging Formatter object.

getFormatter() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer

Returns the logging Formatter object.

getFormatter() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the logging formatter object.

getFrequencyTable() - Method in class com.imsl.stat.TableOneWay

Returns the one-way frequency table.

getFrequencyTable(double, double) - Method in class com.imsl.stat.TableOneWay

Returns a one-way frequency table using known bounds.

getFrequencyTable() - Method in class com.imsl.stat.TableTwoWay

Returns the two-way frequency table.

getFrequencyTable(double, double, double, double) - Method in class com.imsl.stat.TableTwoWay

Compute a two-way frequency table using intervals of equal length and user supplied upper and lower bounds, xLowerBound, xUpperBound, yLowerBound, yUpperBound.

getFrequencyTableUsingClassmarks(double[]) - Method in class com.imsl.stat.TableOneWay

Returns the one-way frequency table using class marks.

getFrequencyTableUsingClassmarks(double[], double[]) - Method in class com.imsl.stat.TableTwoWay

Returns the two-way frequency table using either cutpoints or class marks.

getFrequencyTableUsingCutpoints(double[]) - Method in class com.imsl.stat.TableOneWay

Returns the one-way frequency table using cutpoints.

getFrequencyTableUsingCutpoints(double[], double[]) - Method in class com.imsl.stat.TableTwoWay

Returns the two-way frequency table using cutpoints.

getFrom() - Method in class com.imsl.datamining.neural.Link

Returns the origination Node for this Link.

getGSquared() - Method in class com.imsl.stat.ContingencyTable

Returns the likelihood ratio G² (chi-squared).

getGSquaredP() - Method in class com.imsl.stat.ContingencyTable

Returns the probability of a larger G² (chi-squared).

getGradient() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Gradient" attribute.

getGrid() - Method in class com.imsl.chart.Axis1D

Returns the grid node associated with this axis.

getGridPolar() - Method in class com.imsl.chart.Polar

Returns the grid.

getGroupCounts() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the group counts.

getGroupInformation() - Method in class com.imsl.stat.ANOVA

Returns information concerning the groups.

getGroups() - Method in class com.imsl.stat.TableMultiWay

Returns the number of observations (rows) in each group.

getHREF() - Method in class com.imsl.chart.ChartNode

Returns the value of the "HREF" attribute.

getHREF() - Method in class com.imsl.chart.DrawMap

Returns the current HREF string.

getHeatmapLabels() - Method in class com.imsl.chart.Heatmap

Returns the value of the "HeatmapLabels" attribute.

getHeatmapLegend() - Method in class com.imsl.chart.Heatmap

Returns the heatmap legend.

getHessian() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the Hessian computed at the initial parameter estimates.

getHiddenLayers() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the HiddenLayers in this network.

getHigh() - Method in class com.imsl.chart.ErrorBar

Convenience routine to get the "High" attribute.

getHigh() - Method in class com.imsl.chart.HighLowClose

Convenience routine to get the "High" attribute.

getHistory() - Method in class com.imsl.stat.StepwiseRegression

Returns the stepwise regression history for the independent variables.

getId() - Method in class com.imsl.chart.JspBean

Returns the identifier number for the chart.

getImage() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Image" attribute.

getImageMap() - Method in class com.imsl.chart.JspBean

Returns an HTML for the client-side imagemap.

getImageTag() - Method in class com.imsl.chart.JspBean

Returns an HTML image tag.

getIncidenceMatrix() - Method in class com.imsl.stat.Covariances

Returns the incidence matrix.

getIndependentVariables(int) - Method in class com.imsl.stat.SelectionRegression.Statistics

Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by SelectionRegression.Statistics.getCriterionValues(int).

getIndex() - Method in class com.imsl.datamining.neural.Layer

Returns the index of this Layer.

getInfo() - Method in class com.imsl.math.SVD

Returns convergence information about S, U, and V.

getInputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the InputLayer.

getInputLayer() - Method in class com.imsl.datamining.neural.Network

Returns the InputLayer object.

getInt(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.

getInt(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.

getIntegerAttribute(String, int) - Method in class com.imsl.chart.ChartNode

Convenience routine to get an Integer-valued attribute.

getIterations() - Method in class com.imsl.math.MinUnconMultiVar

Returns the number of iterations used to compute a minimum.

getIterations(int) - Method in class com.imsl.math.ZeroFunction

Returns the number of iterations used to compute a root.

getJacobian() - Method in class com.imsl.math.BoundedLeastSquares

Returns the Jacobian at the approximate solution.

getKnots() - Method in class com.imsl.math.BSpline

Returns a copy of the knot sequence.

getKurtosis() - Method in class com.imsl.stat.Summary

Returns the kurtosis.

getLabelType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "LabelType" attribute.

getLabels() - Method in class com.imsl.chart.AxisLabel

Returns the "Labels" attribute.

getLabels() - Method in class com.imsl.chart.AxisRLabel

Returns the "Labels" attribute.

getLagrangeMultiplerEst() - Method in class com.imsl.math.MinConGenLin

Deprecated. Method name misspelled. Replaced by method getLagrangeMultiplierEst. Returns the Lagrange multiplier estimates of the final active constraints.

getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConGenLin

Returns the Lagrange multiplier estimates of the final active constraints.

getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConNLP

Returns the Lagrange multiplier estimates of the constraints.

getLastParameterUpdates() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the last parameter updates (excluding step halvings).

getLayer() - Method in class com.imsl.datamining.neural.Node

Returns the Layer in which this Node exists.

getLegend() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Legend" attribute.

getLicensePath() - Method in class com.imsl.LicenseManagerException

Returns the license file path for this exception.

getLineColor() - Method in class com.imsl.chart.ChartNode

Returns the value of the "LineColor" attribute.

getLineDashPattern() - Method in class com.imsl.chart.ChartNode

Returns the value of the "LineDashPattern" attribute.

getLineWidth() - Method in class com.imsl.chart.ChartNode

Returns the value of the "LineWidth" attribute.

getLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Return all of the Links in this Network.

getLinks() - Method in class com.imsl.datamining.neural.Network

Returns an array containing the Link objects in the Network.

getListCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable

Returns for each row, a list of the levels of nKeys corresponding classification variables that describe a cell.

getLocale() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Locale" attribute.

getLocalizedMessage() - Method in class com.imsl.LicenseManagerException

Returns the localized error message for this exception.

getLogDeterminant() - Method in class com.imsl.stat.KalmanFilter

Returns the natural log of the product of the nonzero eigenvalues of P where P * sigma² is the variance-covariance matrix of the observations.

getLogLikelihood() - Method in class com.imsl.stat.GARCH

Returns the value of Log-likelihood function evaluated at the estimated parameter array.

getLogger() - Static method in class com.imsl.datamining.neural.EpochTrainer

Returns the Logger object.

getLogger() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer

Returns the Logger object.

getLogger() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the Logger object.

getLogger() - Method in class com.imsl.math.MinConNLP

Returns the logger object.

getLong(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.

getLong(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.

getLow() - Method in class com.imsl.chart.ErrorBar

Convenience routine to get the "Low" attribute.

getLow() - Method in class com.imsl.chart.HighLowClose

Convenience routine to get the "Low" attribute.

getLowerAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the lower adjacent value.

getLowerCICommonVariance() - Method in class com.imsl.stat.NormTwoSample

Returns the lower confidence limits for the common, or pooled, variance.

getLowerCIDiff() - Method in class com.imsl.stat.NormTwoSample

Returns the lower confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.

getLowerCIMean() - Method in class com.imsl.stat.NormOneSample

Returns the lower confidence limit for the mean.

getLowerCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample

Returns the approximate lower confidence limit for the ratio of the variance of the first population to the second.

getLowerCIVariance() - Method in class com.imsl.stat.NormOneSample

Returns the lower confidence limits for the variance.

getLowerQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the lower quartile value.

getMA() - Method in class com.imsl.stat.ARMA

Returns the final moving average parameter estimates.

getMA() - Method in class com.imsl.stat.GARCH

Returns the estimated values of moving average (MA) parameters.

getMahalanobis() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the Mahalanobis distances between the group means.

getMajorTick() - Method in class com.imsl.chart.Axis1D

Returns the major tick node associated with this axis.

getMap() - Method in class com.imsl.chart.DrawMap

Returns the body of the HTML imagemap.

getMapName() - Method in class com.imsl.chart.JspBean

Returns the name of the client-size imagemap.

getMarkerColor() - Method in class com.imsl.chart.ChartNode

Returns the value of the "MarkerColor" attribute.

getMarkerDashPattern() - Method in class com.imsl.chart.ChartNode

Returns the value of the "MarkerPattern" attribute.

getMarkerSize() - Method in class com.imsl.chart.ChartNode

Returns the value of the "MarkerSize" attribute.

getMarkerThickness() - Method in class com.imsl.chart.ChartNode

Returns the value of the "MarkerThickness" attribute.

getMarkerType() - Method in class com.imsl.chart.ChartNode

Returns the value of the "MarkerType" attribute.

getMaxDifference() - Method in class com.imsl.stat.NormalityTest

Returns the maximum absolute difference between the empirical and the theoretical distributions for the Lilliefors test.

getMaximum() - Method in class com.imsl.stat.Summary

Returns the maximum.

getMaximum() - Method in class com.imsl.stat.TableOneWay

Returns maximum value of x.

getMaximumValue() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the maximum value of the observations.

getMaximumX() - Method in class com.imsl.stat.TableTwoWay

Returns the maximum value of x.

getMaximumY() - Method in class com.imsl.stat.TableTwoWay

Returns the maximum value of y.

getMean() - Method in class com.imsl.stat.AutoCorrelation

Returns the mean of the time series x.

getMean() - Method in class com.imsl.stat.NormOneSample

Returns the mean of the sample.

getMean() - Method in class com.imsl.stat.Summary

Returns the population mean.

getMeanEstimate() - Method in class com.imsl.stat.ARMA

Returns an update of the mean of the time series z.

getMeanOfY() - Method in class com.imsl.stat.ANOVA

Returns the mean of the response (dependent variable).

getMeanX() - Method in class com.imsl.stat.CrossCorrelation

Returns the mean of the time series x.

getMeanX() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the mean of each channel of x.

getMeanX() - Method in class com.imsl.stat.NormTwoSample

Returns the mean of the first sample, x.

getMeanY() - Method in class com.imsl.stat.CrossCorrelation

Returns the mean of the time series y.

getMeanY() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the mean of each channel of y.

getMeanY() - Method in class com.imsl.stat.NormTwoSample

Returns the mean of the second sample, y.

getMeans() - Method in class com.imsl.stat.ANOVAFactorial

Returns the subgroup means.

getMeans() - Method in class com.imsl.stat.Covariances

Returns the means of the variables in x.

getMeans() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the variable means.

getMedian() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the median value.

getMedianLowerConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the lower confidence interval for the median.

getMedianUpperConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the upper confidence interval for the median.

getMetaData() - Method in class com.imsl.io.AbstractFlatFile

Retrieves the number, types and properties of this ResultSet object's columns.

getMinimum() - Method in class com.imsl.stat.Summary

Returns the minimum.

getMinimum() - Method in class com.imsl.stat.TableOneWay

Returns the minimum value of x.

getMinimumValue() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the minimum value of the observations.

getMinimumX() - Method in class com.imsl.stat.TableTwoWay

Returns the minimum value of x.

getMinimumY() - Method in class com.imsl.stat.TableTwoWay

Returns the minimum value of y.

getMinorTick() - Method in class com.imsl.chart.Axis1D

Returns the minor tick node associated with this axis.

getModelErrorStdev() - Method in class com.imsl.stat.ANOVA

Returns the estimated standard deviation of the model error.

getModelMeanSquare() - Method in class com.imsl.stat.ANOVA

Returns the model mean square.

getMonthBasis() - Method in class com.imsl.finance.DayCountBasis

Returns the (days in month) portion of the Day Count Basis.

getNCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable

Returns the number of non-empty cells.

getNRowsMissing() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the number of rows of data in x that contain missing values in one or more specific columns of x.

getNRowsMissing() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the number of rows of data encountered containing missing values (NaN).

getName() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Name" attribute.

getNode() - Method in class com.imsl.chart.PickEvent

Gets this ChartNode.

getNodes() - Method in class com.imsl.datamining.neural.InputLayer

Return the Perceptrons in the InputLayer.

getNodes() - Method in class com.imsl.datamining.neural.Layer

Return a list of the Perceptrons in this Layer.

getNodes() - Method in class com.imsl.datamining.neural.OutputLayer

Return the Perceptrons in the OutputLayer.

getNormalScores(double[]) - Method in class com.imsl.stat.Ranks

Gets the expected value of normal order statistics (for tied observations, the average of the expected normal scores).

getNotch() - Method in class com.imsl.chart.BoxPlot

Gets the "Notch" attribute value.

getNumPositiveDev() - Method in class com.imsl.stat.SignTest

Returns the number of positive differences.

getNumRowMissing() - Method in class com.imsl.stat.Covariances

Returns the total number of observations that contain any missing values (Double.NaN).

getNumZeroDev() - Method in class com.imsl.stat.SignTest

Returns the number of zero differences.

getNumber() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Number" attribute.

getNumberFormat() - Method in class com.imsl.math.PrintMatrixFormat

Returns the NumberFormat to be used in formatting double and Complex entries.

getNumberObservations() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the number of observations.

getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter

Retrieves the number of classes in the nominal variable.

getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Retrieves the number of categories associated with this ordinal variable.

getNumberOfEpochs() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the number of epochs used during stage I training.

getNumberOfInputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the number of inputs to the Network.

getNumberOfInputs() - Method in class com.imsl.datamining.neural.Network

Returns the number of Network inputs.

getNumberOfLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the number of Links in the Network.

getNumberOfLinks() - Method in class com.imsl.datamining.neural.Network

Returns the number of Network Links among the nodes.

getNumberOfOutputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the number of outputs from the Network.

getNumberOfOutputs() - Method in class com.imsl.datamining.neural.Network

Returns the number of Network output Perceptrons.

getNumberOfWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the number of weights in the Network.

getNumberOfWeights() - Method in class com.imsl.datamining.neural.Network

Returns the number of weights in the Network.

getNvalues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable

Returns an array of length nKeys containing in its i-th element (i=0,1,...nKeys-1), the number of levels or categories of the i-th classification variable (column).

getObject(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.

getObject(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.

getObject(int, Map) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.

getObject(String, Map) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.

getObject(int) - Method in class com.imsl.io.FlatFile

Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.

getObjectiveValue() - Method in class com.imsl.math.MinConGenLin

Returns the value of the objective function.

getObsPerCluster(int) - Method in class com.imsl.stat.ClusterHierarchical

Returns the number of observations in each cluster.

getObservations() - Method in class com.imsl.stat.Covariances

Returns the sum of the frequencies.

getObservationsLost() - Method in class com.imsl.stat.Difference

Returns the number of observations lost because of differencing the time series.

getOffset() - Method in class com.imsl.chart.Text

Returns the offset.

getOpen() - Method in class com.imsl.chart.HighLowClose

Gets the value of the attribute "Open".

getOptimalValue() - Method in class com.imsl.math.LinearProgramming

Returns the optimal value of the objective function.

getOptimizedCriterion() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the optimized criterion.

getOutputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the OutputLayer.

getOutputLayer() - Method in class com.imsl.datamining.neural.Network

Returns the OutputLayer.

getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the array of outside markers.

getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot

Returns the OutsideMarkers node.

getP() - Method in class com.imsl.stat.ANOVA

Returns the p-value.

getP() - Method in class com.imsl.stat.ChiSquaredTest

Returns the p-value for the chi-squared statistic.

getP() - Method in class com.imsl.stat.ContingencyTable

Returns the Pearson chi-squared p-value for independence of rows and columns.

getPValue(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests

Returns the p-value for the two-sided test.

getPValue(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests

Returns the p-value for the two-sided test vs.

getPaint() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Paint" attribute.

getPanel() - Method in class com.imsl.chart.JFrameChart

Returns the JPanelChart into which the chart is drawn.

getParamEstimatesCovariance() - Method in class com.imsl.stat.ARMA

Returns the covariances of parameter estimates.

getParameterUpdates() - Method in class com.imsl.stat.FactorAnalysis

Returns the parameter updates.

getParameters() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the parameter estimates and associated statistics.

getParent() - Method in class com.imsl.chart.ChartNode

Returns the parent of this node.

getPartialAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation

Returns the sample partial autocorrelation function of the stationary time series x.

getPercentages() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Retrieves the cumulative percentages used for encoding and decoding.

getPercents() - Method in class com.imsl.stat.FactorAnalysis

Returns the cumulative percent of the total variance explained by each principal component.

getPerceptrons() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the Perceptrons in this Network.

getPerceptrons() - Method in class com.imsl.datamining.neural.Network

Returns an array containing the Perceptrons in the Network.

getPermute() - Method in class com.imsl.math.QR

Returns an integer vector containing information about the permutation of the elements of the matrix during pivoting.

getPhi() - Method in class com.imsl.stat.ContingencyTable

Returns phi.

getPieSlice() - Method in class com.imsl.chart.Pie

Returns the PieSlice objects.

getPieSlice(int) - Method in class com.imsl.chart.Pie

Returns a specified PieSlice.

getPooledVariance() - Method in class com.imsl.stat.NormTwoSample

Returns the Pooled variance for the two samples.

getPredictionError() - Method in class com.imsl.stat.KalmanFilter

Returns the one-step-ahead prediction error.

getPrimalSolution() - Method in class com.imsl.math.LinearProgramming

Returns the solution x of the linear programming problem.

getPrior() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the prior probabilities.

getProbability() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns the posterior probabilities for each observation.

getProduct() - Method in class com.imsl.stat.CategoricalGenLinModel

Returns the inverse of the Hessian times the gradient vector computed at the input parameter estimates.

getPsiWeights() - Method in class com.imsl.stat.ARMA

Returns the psi weights of the infinite order moving average form of the model.

getQ() - Method in class com.imsl.math.QR

Returns the orthogonal or unitary matrix Q.

getR() - Method in class com.imsl.math.Cholesky

Returns the R matrix that results from the Cholesky factorization.

getR() - Method in class com.imsl.math.QR

Returns the upper trapezoidal matrix R.

getR() - Method in class com.imsl.stat.LinearRegression

Returns a copy of the R matrix.

getR() - Method in class com.imsl.stat.NonlinearRegression

Returns a copy of the R matrix.

getRSquared() - Method in class com.imsl.stat.ANOVA

Returns the R-squared (in percent).

getRadialFunction() - Method in class com.imsl.math.RadialBasis

Returns the radial function.

getRadius(int) - Method in class com.imsl.math.ZeroPolynomial

Returns an a-posteriori absolute error bound on the root.

getRandom() - Method in class com.imsl.datamining.neural.EpochTrainer

Returns the random number generator used to perturb the stage 1 guesses.

getRank() - Method in class com.imsl.math.QR

Returns the rank of the matrix used to construct this instance.

getRank() - Method in class com.imsl.math.SVD

Returns the rank of the matrix used to construct this instance.

getRank() - Method in class com.imsl.stat.KalmanFilter

Returns the rank of the variance-covariance matrix for all the observations.

getRank() - Method in class com.imsl.stat.LinearRegression

Returns the rank of the matrix.

getRank() - Method in class com.imsl.stat.NonlinearRegression

Returns the rank of the matrix.

getRanks(double[]) - Method in class com.imsl.stat.Ranks

Gets the rank for each observation.

getRef(int) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.

getRef(String) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.

getReference() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Reference" attribute.

getResidual() - Method in class com.imsl.stat.ARMA

Returns the residuals.

getResiduals() - Method in class com.imsl.math.BoundedLeastSquares

Returns the residuals at the approximate solution.

getRoot(int) - Method in class com.imsl.math.ZeroPolynomial

Returns a zero of the polynomial.

getRoots() - Method in class com.imsl.math.ZeroPolynomial

Returns the zeros of the polynomial.

getRow() - Method in class com.imsl.io.AbstractFlatFile

Retrieves the current row number.

getS() - Method in class com.imsl.math.SVD

Returns the singular values.

getSSE() - Method in class com.imsl.stat.NonlinearRegression

Returns the sums of squares for error.

getSSResidual() - Method in class com.imsl.stat.ARMA

Returns the sum of squares of the random shock.

getSampleStandardDeviation() - Method in class com.imsl.stat.Summary

Returns the sample standard deviation.

getSampleVariance() - Method in class com.imsl.stat.Summary

Returns the sample variance.

getSavageScores(double[]) - Method in class com.imsl.stat.Ranks

Gets the Savage scores (the expected value of exponential order statistics).

getScaleFont() - Method in class com.imsl.chart.Draw

Returns the factor by which fonts are to be scaled.

getScreenAxis() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ScreenAxis" attribute.

getScreenSize() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ScreenSize" attribute.

getScreenViewport() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Viewport" attribute scaled by the screen size.

getShapiroWilkW() - Method in class com.imsl.stat.NormalityTest

Returns the Shapiro-Wilk W statistic for the Shapiro-Wilk W test.

getShort(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.

getShort(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.

getSigma() - Method in class com.imsl.stat.GARCH

Returns the estimated value of sigma squared.

getSize() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Size" attribute.

getSize(Text) - Method in class com.imsl.chart.Draw

Returns the size of the bounding box for a text object.

getSize() - Method in class com.imsl.chart.JspBean

Returns the size of the generated image.

getSkewness() - Method in class com.imsl.stat.Summary

Returns the skewness.

getSkip() - Method in class com.imsl.stat.FaureSequence

Returns the number of points skipped at the beginning of the sequence.

getSkipWeekends() - Method in class com.imsl.chart.ChartNode

Returns the value of the "SkipWeekends" attribute.

getSolution() - Method in class com.imsl.math.BoundedLeastSquares

Returns the solution.

getSolution() - Method in class com.imsl.math.MinConGenLin

Returns the computed solution.

getSolution() - Method in class com.imsl.math.QuadraticProgramming

Returns the solution.

getSpline() - Method in class com.imsl.math.BSpline

Returns a Spline representation of the B-spline.

getSpread() - Method in class com.imsl.datamining.neural.ScaleFilter

Retrieves the measure of spread to be used during scaling.

getStandardDeviation() - Method in class com.imsl.stat.Summary

Returns the population standard deviation.

getStandardError(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests

Returns the estimated standard error for a coefficient estimate.

getStandardError(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests

Returns the estimated standard error for a coefficient estimate.

getStandardErrors(int) - Method in class com.imsl.stat.AutoCorrelation

Returns the standard errors of the autocorrelations of the time series x.

getStandardErrors(int) - Method in class com.imsl.stat.CrossCorrelation

Returns the standard errors of the cross-correlations between the time series x and y.

getStandardErrors() - Method in class com.imsl.stat.FactorAnalysis

Returns the estimated asymptotic standard errors of the eigenvalues.

getStateVector() - Method in class com.imsl.stat.KalmanFilter

Returns the estimated state vector at time k + 1 given the observations through time k.

getStatement() - Method in class com.imsl.io.AbstractFlatFile

Returns the Statement object that produced this ResultSet object.

getStatistics() - Method in class com.imsl.chart.BoxPlot

Returns an array of BoxPlot.Statistics objects, one for each set of observations.

getStatistics(int) - Method in class com.imsl.chart.BoxPlot

Returns a BoxPlot.Statistics for a set of observations.

getStatistics() - Method in class com.imsl.stat.ContingencyTable

Returns the statistics associated with this table.

getStatistics() - Method in class com.imsl.stat.DiscriminantAnalysis

Returns statistics.

getStatistics() - Method in class com.imsl.stat.FactorAnalysis

Returns statistics.

getStatistics() - Method in class com.imsl.stat.SelectionRegression

Returns a new Statistics object.

getStatistics() - Method in class com.imsl.stat.WilcoxonRankSum

Returns the statistics.

getStatus(int) - Method in class com.imsl.math.ZeroPolynomial

Returns the error status of a root.

getStdDev() - Method in class com.imsl.stat.NormOneSample

Returns the standard deviation of the sample.

getStdDevX() - Method in class com.imsl.stat.NormTwoSample

Returns the standard deviation of the first sample.

getStdDevY() - Method in class com.imsl.stat.NormTwoSample

Returns the standard deviation of the second sample.

getString() - Method in class com.imsl.chart.Text

Gets the string for this Text object.

getString(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.

getString(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.

getStringAttribute(String) - Method in class com.imsl.chart.ChartNode

Convenience routine to get a String-valued attribute.

getSumOfSquares() - Method in class com.imsl.stat.KalmanFilter

Returns the generalized sum of squares.

getSumOfSquaresForError() - Method in class com.imsl.stat.ANOVA

Returns the sum of squares for error.

getSumOfSquaresForModel() - Method in class com.imsl.stat.ANOVA

Returns the sum of squares for model.

getSumOfWeights() - Method in class com.imsl.stat.Covariances

Returns the sum of the weights of all observations.

getSwept() - Method in class com.imsl.stat.StepwiseRegression

Returns an array containing information indicating whether or not a particular variable is in the model.

getTStatistic(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests

Returns the t-statistic for the test that the i-th coefficient is zero.

getTStatistic(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests

Returns the student-t test statistic for testing the i-th coefficient equal to zero ().

getTTest() - Method in class com.imsl.stat.NormOneSample

Returns the test statistic associated with the t test.

getTTest() - Method in class com.imsl.stat.NormTwoSample

Returns the test statistic for the Satterthwaite's approximation.

getTTestDF() - Method in class com.imsl.stat.NormOneSample

Returns the degrees of freedom associated with the t test for the mean.

getTTestDF() - Method in class com.imsl.stat.NormTwoSample

Returns the degrees of freedom for the Satterthwaite's approximation for t-test for either equal or unequal variances, depending on the value set by setUnequalVariances.

getTTestP() - Method in class com.imsl.stat.NormOneSample

Returns the probability associated with the t test of a larger t in absolute value.

getTTestP() - Method in class com.imsl.stat.NormTwoSample

Returns the approximate probability of a larger t for the Satterthwaite's approximation for equal or unequal variances.

getTable() - Method in class com.imsl.stat.TableMultiWay.BalancedTable

Returns an array containing the frequencies for each variable.

getTable() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable

Returns the frequency for each cell.

getTestEffects() - Method in class com.imsl.stat.ANOVAFactorial

Returns statistics relating to the sums of squares for the effects in the model.

getTextAngle() - Method in class com.imsl.chart.ChartNode

Returns the value of the "TextAngle" attribute.

getTextColor() - Method in class com.imsl.chart.ChartNode

Returns the value of the "TextColor" attribute.

getTextFormat() - Method in class com.imsl.chart.ChartNode

Returns the value of the "TextFormat" attribute.

getTickInterval() - Method in class com.imsl.chart.Axis1D

Retrieves the tick interval.

getTickInterval() - Method in class com.imsl.chart.AxisR

Retrieves the tick interval.

getTickLength() - Method in class com.imsl.chart.ChartNode

Returns the value of the "TickLength" attribute.

getTicks() - Method in class com.imsl.chart.Axis1D

Returns the value of the "Ticks" attribute, if set.

getTicks() - Method in class com.imsl.chart.AxisR

Returns the value of the "Ticks" attribute, if set.

getTicks() - Method in class com.imsl.chart.AxisTheta

Returns the value of the "Ticks" attribute, if set.

getTime(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.

getTime(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.

getTime(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.

getTime(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.

getTimestamp(int) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.

getTimestamp(String) - Method in class com.imsl.io.AbstractFlatFile

Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object.

getTimestamp(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.

getTimestamp(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile

Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.

getTitle() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Title" attribute.

getTo() - Method in class com.imsl.datamining.neural.Link

Returns the destination Node for this Link.

getTolerance() - Method in class com.imsl.chart.DrawMap

Get the minimum distance that an event can be from a point or a line and still be considered a hit.

getTolerance() - Method in class com.imsl.chart.DrawPick

Get the minimum distance that an event can be from a point or a line and still be considered a hit.

getToolTip() - Method in class com.imsl.chart.ChartNode

Returns the value of the "ToolTip" attribute.

getTotalDegreesOfFreedom() - Method in class com.imsl.stat.ANOVA

Returns the total degrees of freedom.

getTotalMissing() - Method in class com.imsl.stat.ANOVA

Returns the total number of missing values.

getTotalSumOfSquares() - Method in class com.imsl.stat.ANOVA

Returns the total sum of squares.

getTrainingIterations() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer

Returns the number of iterations used during training.

getTransform() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Transform" attribute.

getTransform() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter

Retrieves the transform flag used for encoding and decoding.

getTukeyScores(double[]) - Method in class com.imsl.stat.Ranks

Gets the Tukey version of normal scores for each observation.

getType() - Method in class com.imsl.chart.Axis1D

Returns the axis type.

getType() - Method in class com.imsl.chart.Grid

Returns the axis type.

getType() - Method in class com.imsl.io.AbstractFlatFile

Returns the type of this ResultSet object.

getU() - Method in class com.imsl.math.SVD

Returns the left singular vectors.

getURL(String) - Method in class com.imsl.io.AbstractFlatFile

Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.

getURL(int) - Method in class com.imsl.io.AbstractFlatFile

Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.

getUnbalancedTable() - Method in class com.imsl.stat.TableMultiWay

Returns an object containing the unbalanced table.

getUnicodeStream(int) - Method in class com.imsl.io.AbstractFlatFile

Deprecated. use getCharacterStream in place of getUnicodeStream

getUnicodeStream(String) - Method in class com.imsl.io.AbstractFlatFile

Deprecated.

getUp() - Method in class com.imsl.chart.Candlestick

Returns the CandlestickItem for up days.

getUpperAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the lower adjacent value.

getUpperCICommonVariance() - Method in class com.imsl.stat.NormTwoSample

Returns the upper confidence limits for the common, or pooled, variance.

getUpperCIDiff() - Method in class com.imsl.stat.NormTwoSample

Returns the upper confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.

getUpperCIMean() - Method in class com.imsl.stat.NormOneSample

Returns the upper confidence limit for the mean.

getUpperCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample

Returns the approximate upper confidence limit for the ratio of the variance of the first population to the second.

getUpperCIVariance() - Method in class com.imsl.stat.NormOneSample

Returns the upper confidence limits for the variance.

getUpperQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics

Returns the upper quartile value.

getV() - Method in class com.imsl.math.SVD

Returns the right singular vectors.

getValue() - Method in class com.imsl.datamining.neural.InputNode

Returns the value of this node.

getValue() - Method in class com.imsl.datamining.neural.OutputPerceptron

Returns the value of the output perceptron determined using the current network state and inputs.

getValues() - Method in class com.imsl.math.Eigen

Returns the eigenvalues of a matrix of type double.

getValues() - Method in class com.imsl.math.SymEigen

Returns the eigenvalues

getValues() - Method in class com.imsl.stat.FactorAnalysis

Returns the eigenvalues.

getValues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable

Returns the values of the classification variables.

getVanDerWaerdenScores(double[]) - Method in class com.imsl.stat.Ranks

Gets the Van der Waerden version of normal scores for each observation.

getVarCovarMatrix() - Method in class com.imsl.stat.GARCH

Returns the variance-covariance matrix.

getVariance() - Method in class com.imsl.stat.ARMA

Returns the variance of the time series z.

getVariance() - Method in class com.imsl.stat.AutoCorrelation

Returns the variance of the time series x.

getVariance() - Method in class com.imsl.stat.Summary

Returns the population variance.

getVarianceX() - Method in class com.imsl.stat.CrossCorrelation

Returns the variance of time series x.

getVarianceX() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the variances of the channels of x.

getVarianceY() - Method in class com.imsl.stat.CrossCorrelation

Returns the variance of time series y.

getVarianceY() - Method in class com.imsl.stat.MultiCrossCorrelation

Returns the variances of the channels of y.

getVariances() - Method in class com.imsl.stat.FactorAnalysis

Gets the unique variances.

getVectors() - Method in class com.imsl.math.Eigen

Returns the eigenvectors.

getVectors() - Method in class com.imsl.math.SymEigen

Return the eigenvectors of a symmetric matrix of type double.

getVectors() - Method in class com.imsl.stat.FactorAnalysis

Returns the eigenvectors.

getViewport() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Viewport" attribute.

getWarning() - Static method in class com.imsl.Warning

Gets the WarningObject.

getWarnings() - Method in class com.imsl.io.AbstractFlatFile

Returns the first warning reported by calls on this ResultSet object.

getWeight() - Method in class com.imsl.datamining.neural.Link

Returns the weight for this Link.

getWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Returns the weights for the Links in this network.

getWeights() - Method in class com.imsl.datamining.neural.Network

Returns the weights.

getWhiskers() - Method in class com.imsl.chart.BoxPlot

Returns the Whiskers node.

getWindow() - Method in class com.imsl.chart.Axis1D

Returns the window for an Axis1D.

getWindow() - Method in class com.imsl.chart.AxisR

Returns the Window attribute.

getWindow() - Method in class com.imsl.chart.AxisTheta

Returns the window for an AxisTheta.

getX() - Method in class com.imsl.chart.ChartNode

Returns the value of the "X" attribute.

getX() - Method in class com.imsl.stat.GARCH

Returns the estimated parameter array, x.

getY() - Method in class com.imsl.chart.ChartNode

Returns the value of the "Y" attribute.

getYearBasis() - Method in class com.imsl.finance.DayCountBasis

Returns the (days in year) portion of the Day Count Basis.

gradient(double[], double[]) - Method in interface com.imsl.math.MinConGenLin.Gradient

Public interface for the user-supplied function to compute the gradient at point x.

gradient(double[], int, double[]) - Method in interface com.imsl.math.MinConNLP.Gradient

Computes the value of the gradient of the function at the given point.

gradient(double[], double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Gradient

Public interface for the gradient of the multivariate function to be minimized.

gradient(double[]) - Method in class com.imsl.math.RadialBasis

Returns the gradient of the radial basis approximation at a point.

graphics - Variable in class com.imsl.chart.Draw

H

Heatmap - class com.imsl.chart.Heatmap.

Heatmap creates a chart from a two-dimensional array of double precision values or Color values.

Heatmap(AxisXY, double, double, double, double, Color[][]) - Constructor for class com.imsl.chart.Heatmap

Creates a Heatmap from an array of Color values.

Heatmap(AxisXY, double, double, double, double, double, double, double[][], Colormap) - Constructor for class com.imsl.chart.Heatmap

Creates a Heatmap from an array of double values and a Colormap.

Heatmap.Legend - class com.imsl.chart.Heatmap.Legend.

A legend for use with a heatmap.

HiddenLayer - class com.imsl.datamining.neural.HiddenLayer.

Hidden layer in a neural network.

HighLowClose - class com.imsl.chart.HighLowClose.

High-low-close plot of stock data.

HighLowClose(AxisXY, Date, double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose

Constructs a high-low-close chart node beginning with specified start date.

HighLowClose(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose

Constructs a high-low-close-open chart node beginning with specified start date.

HighLowClose(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose

Constructs a high-low-close chart node at specified axis points.

HighLowClose(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose

Constructs a high-low-close-open chart node at specified axis points.

HyperRectangleQuadrature - class com.imsl.math.HyperRectangleQuadrature.

HyperRectangleQuadrature integrates a function over a hypercube.

HyperRectangleQuadrature(int) - Constructor for class com.imsl.math.HyperRectangleQuadrature

Constructs a HyperRectangleQuadrature object.

HyperRectangleQuadrature(RandomSequence) - Constructor for class com.imsl.math.HyperRectangleQuadrature

Constructs a HyperRectangleQuadrature object.

HyperRectangleQuadrature.Function - interface com.imsl.math.HyperRectangleQuadrature.Function.

Public interface function for the HyperRectangleQuadrature class.

Hyperbolic - class com.imsl.math.Hyperbolic.

Pure Java implementation of the hyperbolic functions and their inverses.

hasMoreTokens() - Method in class com.imsl.io.Tokenizer

Returns true if a call to nextToken will not generate an exception.

hashCode() - Method in class com.imsl.math.Complex

Returns a hashcode for this Complex.

haveErrorBarProperties - Variable in class com.imsl.chart.Draw

haveFillProperties - Variable in class com.imsl.chart.Draw

haveImageProperties - Variable in class com.imsl.chart.Draw

haveLineProperties - Variable in class com.imsl.chart.Draw

haveMarkerProperties - Variable in class com.imsl.chart.Draw

haveTextProperties - Variable in class com.imsl.chart.Draw

horizontalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint

Returns a horizontally striped pattern.

hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Cdf

Evaluates the hypergeometric distribution function.

hypergeometricProb(int, int, int, int) - Static method in class com.imsl.stat.Cdf

Evaluates the hypergeometric probability function.

I

I(double, int) - Static method in class com.imsl.math.Bessel

Evaluates a sequence of modified Bessel functions of the first kind with integer order and real argument.

I(double, double, int) - Static method in class com.imsl.math.Bessel

Evaluates a sequence of modified Bessel functions of the first kind with real order and real argument.

IEEE - class com.imsl.math.IEEE.

Pure Java implementation of the IEEE 754 functions as specified in IEEE Standard for Binary Floating-Point Arithmetic, ANSI/IEEE Standard 754-1985 (IEEE, New York).

IEEEremainder(double, double) - Static method in class com.imsl.math.JMath

Returns the IEEE remainder from x divided by p.

IMAGE - Static variable in class com.imsl.chart.Draw

IMAGE_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis

Indicates image factor analysis.

IMSLException - exception com.imsl.IMSLException.

Signals that a mathematical exception has occurred.

IMSLException() - Constructor for class com.imsl.IMSLException

Constructs an IMSLException with no detail message.

IMSLException(String) - Constructor for class com.imsl.IMSLException

Constructs an IMSLException with the specified detail message.

IMSLException(String, String, Object[]) - Constructor for class com.imsl.IMSLException

Constructs an IMSLException with the specified detail message.

IMSLRuntimeException - exception com.imsl.IMSLRuntimeException.

Signals that an error has occurred.

IMSLRuntimeException() - Constructor for class com.imsl.IMSLRuntimeException

Constructs an IMSLRuntimeException with no detail message.

IMSLRuntimeException(String) - Constructor for class com.imsl.IMSLRuntimeException

Constructs an IMSLRuntimeException with the specified detail message.

IMSLRuntimeException(String, String, Object[]) - Constructor for class com.imsl.IMSLRuntimeException

Constructs an IMSLRuntimeException with the specified detail message.

InputLayer - class com.imsl.datamining.neural.InputLayer.

Input layer in a neural network.

InputNode - class com.imsl.datamining.neural.InputNode.

A Node in the InputLayer.

InverseCdf - class com.imsl.stat.InverseCdf.

Inverse of user-supplied cumulative distribution function.

InverseCdf(CdfFunction) - Constructor for class com.imsl.stat.InverseCdf

Constructor for the inverse of a user-supplied cummulative distribution function.

InverseCdf.DidNotConvergeException - exception com.imsl.stat.InverseCdf.DidNotConvergeException.

The iteration did not converge

InverseCdf.DidNotConvergeException(String) - Constructor for class com.imsl.stat.InverseCdf.DidNotConvergeException

InverseCdf.DidNotConvergeException(String, Object[]) - Constructor for class com.imsl.stat.InverseCdf.DidNotConvergeException

i - Static variable in class com.imsl.math.Complex

The imaginary unit.

ilogb(double) - Static method in class com.imsl.math.IEEE

Return the binary exponent of non-zero x.

imag() - Method in class com.imsl.math.Complex

Returns the imaginary part of a Complex object.

imag(Complex) - Static method in class com.imsl.math.Complex

Returns the imaginary part of a Complex object.

image(ImageIcon) - Static method in class com.imsl.chart.FillPaint

Returns a tiling of an image.

imageObserver - Variable in class com.imsl.chart.Draw

infinityNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix

Return the infinity norm of a Complex matrix.

infinityNorm(double[][]) - Static method in class com.imsl.math.Matrix

Return the infinity norm of a matrix.

init() - Method in class com.imsl.chart.ChartServlet

insertRow() - Method in class com.imsl.io.AbstractFlatFile

Inserts the contents of the insert row into this ResultSet object and into the database.

intValue() - Method in class com.imsl.math.Complex

Returns the value of the real part as an int.

intValue() - Method in class com.imsl.math.Physical

Returns the value of this dimensionless object.

integral(double, double) - Method in class com.imsl.math.BSpline

Returns the value of an integral of the B-spline.

integral(double, double) - Method in class com.imsl.math.Spline

Returns the value of an integral of the spline.

intrate(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond

Returns the interest rate of a fully invested security.

inverse() - Method in class com.imsl.math.Cholesky

Returns the inverse of this matrix

inverse() - Method in class com.imsl.math.ComplexLU

Compute the inverse of a matrix of type Complex.

inverse() - Method in class com.imsl.math.LU

Returns the inverse of the matrix used to construct this instance.

inverse() - Method in class com.imsl.math.SVD

Compute the Moore-Penrose generalized inverse of a real matrix.

inverseBeta(double, double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the inverse of the beta probability distribution function.

inverseChi(double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the inverse of the chi-squared distribution function.

inverseF(double, double, double) - Static method in class com.imsl.stat.Cdf

Returns inverse of the F probability distribution function.

inverseGamma(double, double) - Static method in class com.imsl.stat.Cdf

Evaluates the inverse of the gamma distribution function.

inverseNormal(double) - Static method in class com.imsl.stat.Cdf

Evaluates the inverse of the normal (Gaussian) distribution function.

inverseStudentsT(double, double) - Static method in class com.imsl.stat.Cdf

Returns inverse of the Student's t distribution function.

ipmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance

Returns the interest payment for an investment for a given period.

ipvt - Variable in class com.imsl.math.ComplexLU

Pivot sequence for the factorization

ipvt - Variable in class com.imsl.math.LU

Pivot sequence for the factorization

irr(double[]) - Static method in class com.imsl.finance.Finance

Returns the internal rate of return for a schedule of cash flows.

irr(double[], double) - Static method in class com.imsl.finance.Finance

Returns the internal rate of return for a schedule of cash flows.

isAfterLast() - Method in class com.imsl.io.AbstractFlatFile

Indicates whether the cursor is after the last row in this ResultSet object.

isAncestorOf(ChartNode) - Method in class com.imsl.chart.ChartNode

Returns true if this node is an ancestor of the argument node.

isAttributeSet(String) - Method in class com.imsl.chart.ChartNode

Determines if an attribute is defined (may have been inherited).

isAttributeSetAtThisNode(String) - Method in class com.imsl.chart.ChartNode

Determines if an attribute is defined in this node (not inherited).

isBeforeFirst() - Method in class com.imsl.io.AbstractFlatFile

Indicates whether the cursor is before the first row in this ResultSet object.

isBitSet(int, int) - Static method in class com.imsl.chart.ChartNode

Returns true if the bit set in flag is set in mask.

isFirst() - Method in class com.imsl.io.AbstractFlatFile

Indicates whether the cursor is on the first row of this ResultSet object.

isLast() - Method in class com.imsl.io.AbstractFlatFile

Indicates whether the cursor is on the last row of this ResultSet object.

isNaN(double) - Static method in class com.imsl.math.IEEE

NaN test on an argument of type double.

isNoMoreProgress() - Method in class com.imsl.math.QuadraticProgramming

Returns true if due to computer rounding error, a change in the variables fail to improve the objective function.

isProportionalWidth() - Method in class com.imsl.chart.BoxPlot

Returns the value of the attribute "ProportionalWidth".

isWeekday(GregorianCalendar) - Method in class com.imsl.chart.TransformDate

Returns true if the specified date is a weekday.

J

J(double, int) - Static method in class com.imsl.math.Bessel

Evaluates a sequence of Bessel functions of the first kind with integer order and real argument.

J(double, double, int) - Static method in class com.imsl.math.Bessel

Evaluate a sequence of Bessel functions of the first kind with real order and real positive argument.

JFrameChart - class com.imsl.chart.JFrameChart.

JFrameChart is a JFrame that contains a chart.

JFrameChart() - Constructor for class com.imsl.chart.JFrameChart

Creates new JFrameChart to display a chart.

JFrameChart(Chart) - Constructor for class com.imsl.chart.JFrameChart

Creates new JFrameChart to display a given chart.

JMath - class com.imsl.math.JMath.

Pure Java implementation of the standard java.lang.Math class.

JPanelChart - class com.imsl.chart.JPanelChart.

A Swing JPanel that contains a chart.

JPanelChart() - Constructor for class com.imsl.chart.JPanelChart

Creates new JPanelChart.

JPanelChart(Chart) - Constructor for class com.imsl.chart.JPanelChart

Creates new JPanelChart using a given Chart object.

JspBean - class com.imsl.chart.JspBean.

JspBean is used to refer to charts in a Java Server Page that are later rendered using the ChartServlet.

JspBean() - Constructor for class com.imsl.chart.JspBean

Creates a JspBean object.

jacobian(double[], double[][]) - Method in interface com.imsl.math.NonlinLeastSquares.Jacobian

Public interface for the nonlinear least squares function.

jacobian(double[], double[][]) - Method in interface com.imsl.math.ZeroSystem.Jacobian

Returns the value of the Jacobian at the given point.

K

K(double, int) - Static method in class com.imsl.math.Bessel

Evaluates a sequence of modified Bessel functions of the third kind with integer order and real argument.

K(double, double, int) - Static method in class com.imsl.math.Bessel

Evaluates a sequence of modified Bessel functions of the third kind with fractional order and real argument.

KalmanFilter - class com.imsl.stat.KalmanFilter.

Performs Kalman filtering and evaluates the likelihood function for the state-space model.

KalmanFilter(double[], double[], int, double, double) - Constructor for class com.imsl.stat.KalmanFilter

Constructor for KalmanFilter.

keySet() - Method in class com.imsl.chart.xml.ChartXML

Returns the Set view of all id's defined in the XML file.

knot - Variable in class com.imsl.math.BSpline

The knot array of length n + order, where n is the number of coefficients in the B-spline.

kurtosis(double[]) - Static method in class com.imsl.stat.Summary

Returns the kurtosis of the given data set.

kurtosis(double[], double[]) - Static method in class com.imsl.stat.Summary

Returns the kurtosis of the given data set and associated weights.

L

LABEL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate the an element is not to be labeled.

LABEL_TYPE_PERCENT - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that a pie slice is to be labeled with a percentage value.

LABEL_TYPE_TITLE - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that an element is to be labeled with the value of its title attribute.

LABEL_TYPE_X - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that an element is to be labeled with the value of its x-coordinate.

LABEL_TYPE_Y - Static variable in class com.imsl.chart.ChartNode

Flag used to indicate that an element is to be labeled with the value of its y-coordinate.

LAST - Static variable in class com.imsl.chart.Draw

Flag for the last data marker.

LEAST_SQUARES - Static variable in class com.imsl.stat.ARMA

Indicates autoregressive and moving average parameters are estimated by a least-squares procedure.

LEAVE_OUT_ONE - Static variable in class com.imsl.stat.DiscriminantAnalysis

Indicates leave-out-one as the Classicfication Method.

LENGTH - Static variable in class com.imsl.math.Physical

LINE - Static variable in class com.imsl.chart.Draw

LINEAR - Static variable in interface com.imsl.datamining.neural.Activation

The identity activation function, g(x) = x.

LINEAR - Static variable in class com.imsl.stat.DiscriminantAnalysis

Indicates a linear discrimination method.

LOGISTIC - Static variable in interface com.imsl.datamining.neural.Activation

The logistic activation function, .

LOGISTIC_TABLE - Static variable in interface com.imsl.datamining.neural.Activation

The logistic activation function computed using a table.

LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix

This flag as the argument to setMatrixType, indicates that only the lower triangular elements of the matrix are to be printed.

LU - class com.imsl.math.LU.

LU factorization of a matrix of type double.

LU(double[][]) - Constructor for class com.imsl.math.LU

Creates the LU factorization of a square matrix of type double.

Layer - class com.imsl.datamining.neural.Layer.

The base class for Layers in a neural network.

Layer(FeedForwardNetwork) - Constructor for class com.imsl.datamining.neural.Layer

Constructs a Layer.

LeastSquaresTrainer - class com.imsl.datamining.neural.LeastSquaresTrainer.

Trains a FeedForwardNetwork using a Levenberg-Marquardt algorithm for minimizing a sum of squares error.

LeastSquaresTrainer() - Constructor for class com.imsl.datamining.neural.LeastSquaresTrainer

Creates a LeastSquaresTrainer.

Legend - class com.imsl.chart.Legend.

The chart legend.

Legend(Chart) - Constructor for class com.imsl.chart.Legend

LicenseManagerException - exception com.imsl.LicenseManagerException.

A LicenseManagerException exception is thrown if a license to use the product cannot be obtained.

LillieforsTest() - Method in class com.imsl.stat.NormalityTest

Performs the Lilliefors test.

LinearProgramming - class com.imsl.math.LinearProgramming.

Linear programming problem using the revised simplex algorithm.

LinearProgramming(double[][], double[], double[]) - Constructor for class com.imsl.math.LinearProgramming

Constructor variables of type double.

LinearProgramming.BoundsInconsistentException - exception com.imsl.math.LinearProgramming.BoundsInconsistentException.

The bounds given are inconsistent.

LinearProgramming.BoundsInconsistentException(String) - Constructor for class com.imsl.math.LinearProgramming.BoundsInconsistentException

LinearProgramming.BoundsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.LinearProgramming.BoundsInconsistentException

LinearProgramming.NumericDifficultyException - exception com.imsl.math.LinearProgramming.NumericDifficultyException.

Numerical difficulty occurred.

LinearProgramming.NumericDifficultyException(String) - Constructor for class com.imsl.math.LinearProgramming.NumericDifficultyException

LinearProgramming.NumericDifficultyException(String, Object[]) - Constructor for class com.imsl.math.LinearProgramming.NumericDifficultyException

LinearProgramming.ProblemInfeasibleException - exception com.imsl.math.LinearProgramming.ProblemInfeasibleException.

The problem is not feasible.

LinearProgramming.ProblemInfeasibleException(String) - Constructor for class com.imsl.math.LinearProgramming.ProblemInfeasibleException

LinearProgramming.ProblemInfeasibleException() - Constructor for class com.imsl.math.LinearProgramming.ProblemInfeasibleException

LinearProgramming.ProblemUnboundedException - exception com.imsl.math.LinearProgramming.ProblemUnboundedException.

The problem is unbounded.

LinearProgramming.ProblemUnboundedException(String) - Constructor for class com.imsl.math.LinearProgramming.ProblemUnboundedException

LinearProgramming.ProblemUnboundedException() - Constructor for class com.imsl.math.LinearProgramming.ProblemUnboundedException

LinearProgramming.WrongConstraintTypeException - exception com.imsl.math.LinearProgramming.WrongConstraintTypeException.

Deprecated. The values for the type of constraint must be either 0, 1 or 2.

LinearProgramming.WrongConstraintTypeException(String) - Constructor for class com.imsl.math.LinearProgramming.WrongConstraintTypeException

Deprecated.

LinearProgramming.WrongConstraintTypeException(String, Object[]) - Constructor for class com.imsl.math.LinearProgramming.WrongConstraintTypeException

Deprecated.

LinearRegression - class com.imsl.stat.LinearRegression.

Fits a multiple linear regression model with or without an intercept.

LinearRegression(int, boolean) - Constructor for class com.imsl.stat.LinearRegression

Constructs a new linear regression object.

LinearRegression.CoefficientTTests - class com.imsl.stat.LinearRegression.CoefficientTTests.

CoefficientTTests contains statistics related to the regression coefficients.

Link - class com.imsl.datamining.neural.Link.

A link in a neural network.

last() - Method in class com.imsl.io.AbstractFlatFile

Moves the cursor to the last row in this ResultSet object.

lineColor - Variable in class com.imsl.chart.Draw

lineDashPattern - Variable in class com.imsl.chart.Draw

lineWidth - Variable in class com.imsl.chart.Draw

link(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Establishes a Link between two Nodes.

link(Node, Node, double) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Establishes a Link between two Nodes with a specified weight.

linkAll(Layer, Layer) - Method in class com.imsl.datamining.neural.FeedForwardNetwork

Link all of the Nodes in one Layer to all of the Nodes in another Layer.

linkAll() - Method in class com.imsl.datamining.neural.FeedForwardNetwork

For each Layer in the Network, link each Node in the Layer to each Node in the next Layer.

log(Complex) - Static method in class com.imsl.math.Complex

Returns the logarithm of a Complex z, with a branch cut along the negative real axis.

log(double) - Static method in class com.imsl.math.JMath

Returns the natural logarithm of a double.

log10(double) - Static method in class com.imsl.math.Sfun

Returns the common (base 10) logarithm of a double.

log1p(double) - Static method in class com.imsl.math.Hyperbolic

Returns log(1+x), the logarithm of (x plus 1).

logBeta(double, double) - Static method in class com.imsl.math.Sfun

Returns the logarithm of the Beta function.

logGamma(double) - Static method in class com.imsl.math.Sfun

Returns the logarithm of the Gamma function of the absolute value of a double.

longValue() - Method in class com.imsl.math.Complex

Returns the value of the real part as a long.

longValue() - Method in class com.imsl.math.Physical

Returns the value of this dimensionless object.

M

MALLOWS_CP_CRITERION - Static variable in class com.imsl.stat.SelectionRegression

Indicates Mallow's criterion regression.

MARKER - Static variable in class com.imsl.chart.Draw

MARKER_SCALE - Static variable in class com.imsl.chart.Draw

Normal marker size in pixels is screen width times MARKER_SCALE.

MARKER_TYPE_ASTERISK - Static variable in class com.imsl.chart.ChartNode

Flag for a asterisk data marker.

MARKER_TYPE_CIRCLE_CIRCLE - Static variable in class com.imsl.chart.ChartNode

Flag for a circle in a circle data marker.

MARKER_TYPE_CIRCLE_PLUS - Static variable in class com.imsl.chart.ChartNode

Flag for a plus in a circle data marker.

MARKER_TYPE_CIRCLE_X - Static variable in class com.imsl.chart.ChartNode

Flag for an x in a circle data marker.

MARKER_TYPE_DIAMOND_PLUS - Static variable in class com.imsl.chart.ChartNode

Flag for a plus in a diamond data marker.

MARKER_TYPE_FILLED_CIRCLE - Static variable in class com.imsl.chart.ChartNode

Flag for a filled circle data marker.

MARKER_TYPE_FILLED_DIAMOND - Static variable in class com.imsl.chart.ChartNode

Flag for a filled diamond data marker.

MARKER_TYPE_FILLED_SQUARE - Static variable in class com.imsl.chart.ChartNode

Flag for a filled square data marker.

MARKER_TYPE_FILLED_TRIANGLE - Static variable in class com.imsl.chart.ChartNode

Flag for a filled triangle data marker.

MARKER_TYPE_HOLLOW_CIRCLE - Static variable in class com.imsl.chart.ChartNode

Flag for a hollow circle data marker.

MARKER_TYPE_HOLLOW_DIAMOND - Static variable in class com.imsl.chart.ChartNode

Flag for a hollow diamond data marker.

MARKER_TYPE_HOLLOW_SQUARE - Static variable in class com.imsl.chart.ChartNode

Flag for a hollow square data marker.

MARKER_TYPE_HOLLOW_TRIANGLE - Static variable in class com.imsl.chart.ChartNode

Flag for hollow triangle data marker.

MARKER_TYPE_OCTAGON_PLUS - Static variable in class com.imsl.chart.ChartNode

Flag for a plus in an octagon data marker.

MARKER_TYPE_OCTAGON_X - Static variable in class com.imsl.chart.ChartNode

Flag for a x in an octagon data marker.

MARKER_TYPE_PLUS - Static variable in class com.imsl.chart.ChartNode

Flag for a plus-shaped data marker.

MARKER_TYPE_SQUARE_PLUS - Static variable in class com.imsl.chart.ChartNode

Flag for a plus in a square data marker.

MARKER_TYPE_SQUARE_X - Static variable in class com.imsl.chart.ChartNode

Flag for an x in a square data marker.

MARKER_TYPE_X - Static variable in class com.imsl.chart.ChartNode

Flag for a x-shaped data marker.

MASS - Static variable in class com.imsl.math.Physical

MAXIMUM_LIKELIHOOD - Static variable in class com.imsl.stat.FactorAnalysis

Indicates maximum likelihood method.

METHOD_OF_MOMENTS - Static variable in class com.imsl.stat.ARMA

Indicates autoregressive and moving average parameters are estimated by a method of moments procedure.

MODEL0 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates an exponential function is used to model the distribution parameter.

MODEL1 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates a logistic function is used to model the distribution parameter.

MODEL2 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates a logistic function is used to model the distribution parameter.

MODEL3 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates a logistic function is used to model the distribution parameter.

MODEL4 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates a probit function is used to model the distribution parameter.

MODEL5 - Static variable in class com.imsl.stat.CategoricalGenLinModel

Indicates a log-log function is used to model the distribution parameter.

MORANS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation

Indicates standard error computation using Moran's formula.

MajorTick - class com.imsl.chart.MajorTick.

The major tick marks.

Matrix - class com.imsl.math.Matrix.

Matrix manipulation functions.

Messages - class com.imsl.Messages.

Retrieve and format message strings.

Messages() - Constructor for class com.imsl.Messages

MinConGenLin - class com.imsl.math.MinConGenLin.

Minimizes a general objective function subject to linear equality/inequality constraints.

MinConGenLin(MinConGenLin.Function, int, int, int, double[], double[], double[], double[]) - Constructor for class com.imsl.math.MinConGenLin

Constructor for MinConGenLin.

MinConGenLin.ConstraintsInconsistentException - exception com.imsl.math.MinConGenLin.ConstraintsInconsistentException.

The equality constraints are inconsistent.

MinConGenLin.ConstraintsInconsistentException(String) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsInconsistentException

MinConGenLin.ConstraintsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsInconsistentException

MinConGenLin.ConstraintsNotSatisfiedException - exception com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException.

No vector x satisfies all of the constraints.

MinConGenLin.ConstraintsNotSatisfiedException(String) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException

MinConGenLin.ConstraintsNotSatisfiedException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException

MinConGenLin.EqualityConstraintsException - exception com.imsl.math.MinConGenLin.EqualityConstraintsException.

the variables are determined by the equality constraints.

MinConGenLin.EqualityConstraintsException(String) - Constructor for class com.imsl.math.MinConGenLin.EqualityConstraintsException

MinConGenLin.EqualityConstraintsException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.EqualityConstraintsException

MinConGenLin.Function - interface com.imsl.math.MinConGenLin.Function.

Public interface for the user-supplied function to evaluate the function to be minimized.

MinConGenLin.Gradient - interface com.imsl.math.MinConGenLin.Gradient.

Public interface for the user-supplied function to compute the gradient.

MinConGenLin.VarBoundsInconsistentException - exception com.imsl.math.MinConGenLin.VarBoundsInconsistentException.

The equality constraints and the bounds on the variables are found to be inconsistent.

MinConGenLin.VarBoundsInconsistentException(String) - Constructor for class com.imsl.math.MinConGenLin.VarBoundsInconsistentException

MinConGenLin.VarBoundsInconsistentException(String, Object[]) - Constructor for class com.imsl.math.MinConGenLin.VarBoundsInconsistentException

MinConNLP - class com.imsl.math.MinConNLP.

General nonlinear programming solver.

MinConNLP(int, int, int) - Constructor for class com.imsl.math.MinConNLP

Nonlinear programming solver constructor.

MinConNLP.BadInitialGuessException - exception com.imsl.math.MinConNLP.BadInitialGuessException.

Penalty function point infeasible for original problem.

MinConNLP.BadInitialGuessException(String) - Constructor for class com.imsl.math.MinConNLP.BadInitialGuessException

MinConNLP.BadInitialGuessException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.BadInitialGuessException

MinConNLP.ConstraintEvaluationException - exception com.imsl.math.MinConNLP.ConstraintEvaluationException.

Constraint evaluation returns an error with current point.

MinConNLP.ConstraintEvaluationException(String) - Constructor for class com.imsl.math.MinConNLP.ConstraintEvaluationException

MinConNLP.ConstraintEvaluationException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.ConstraintEvaluationException

MinConNLP.Formatter - class com.imsl.math.MinConNLP.Formatter.

Simple formatter for MinConNLP logging

MinConNLP.Formatter() - Constructor for class com.imsl.math.MinConNLP.Formatter

MinConNLP.Function - interface com.imsl.math.MinConNLP.Function.

Public interface for the user supplied function to the MinConNLP object.

MinConNLP.Gradient - interface com.imsl.math.MinConNLP.Gradient.

Public interface for the user supplied function to compute the gradient for MinConNLP object.

MinConNLP.IllConditionedException - exception com.imsl.math.MinConNLP.IllConditionedException.

Problem is singular or ill-conditioned.

MinConNLP.IllConditionedException(String) - Constructor for class com.imsl.math.MinConNLP.IllConditionedException

MinConNLP.IllConditionedException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.IllConditionedException

MinConNLP.LimitingAccuracyException - exception com.imsl.math.MinConNLP.LimitingAccuracyException.

Limiting accuracy reached for a singular problem.

MinConNLP.LimitingAccuracyException(String) - Constructor for class com.imsl.math.MinConNLP.LimitingAccuracyException

MinConNLP.LimitingAccuracyException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.LimitingAccuracyException

MinConNLP.LinearlyDependentGradientsException - exception com.imsl.math.MinConNLP.LinearlyDependentGradientsException.

Working set gradients are linearly dependent.

MinConNLP.LinearlyDependentGradientsException(String) - Constructor for class com.imsl.math.MinConNLP.LinearlyDependentGradientsException

MinConNLP.LinearlyDependentGradientsException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.LinearlyDependentGradientsException

MinConNLP.NoAcceptableStepsizeException - exception com.imsl.math.MinConNLP.NoAcceptableStepsizeException.

No acceptable stepsize in [SIGMA,SIGLA].

MinConNLP.NoAcceptableStepsizeException(String) - Constructor for class com.imsl.math.MinConNLP.NoAcceptableStepsizeException

MinConNLP.NoAcceptableStepsizeException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.NoAcceptableStepsizeException

MinConNLP.ObjectiveEvaluationException - exception com.imsl.math.MinConNLP.ObjectiveEvaluationException.

Objective evaluation returns an error with current point.

MinConNLP.ObjectiveEvaluationException(String) - Constructor for class com.imsl.math.MinConNLP.ObjectiveEvaluationException

MinConNLP.ObjectiveEvaluationException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.ObjectiveEvaluationException

MinConNLP.PenaltyFunctionPointInfeasibleException - exception com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException.

Penalty function point infeasible.

MinConNLP.PenaltyFunctionPointInfeasibleException(String) - Constructor for class com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException

MinConNLP.PenaltyFunctionPointInfeasibleException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException

MinConNLP.QPInfeasibleException - exception com.imsl.math.MinConNLP.QPInfeasibleException.

QP problem seemingly infeasible.

MinConNLP.QPInfeasibleException(String) - Constructor for class com.imsl.math.MinConNLP.QPInfeasibleException

MinConNLP.QPInfeasibleException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.QPInfeasibleException

MinConNLP.SingularException - exception com.imsl.math.MinConNLP.SingularException.

Problem is singular.

MinConNLP.SingularException(String) - Constructor for class com.imsl.math.MinConNLP.SingularException

MinConNLP.SingularException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.SingularException

MinConNLP.TerminationCriteriaNotSatisfiedException - exception com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException.

Termination criteria are not satisfied.

MinConNLP.TerminationCriteriaNotSatisfiedException(String) - Constructor for class com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException

MinConNLP.TerminationCriteriaNotSatisfiedException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException

MinConNLP.TooManyIterationsException - exception com.imsl.math.MinConNLP.TooManyIterationsException.

Maximum number of iterations exceeded.

MinConNLP.TooManyIterationsException(String) - Constructor for class com.imsl.math.MinConNLP.TooManyIterationsException

MinConNLP.TooManyIterationsException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.TooManyIterationsException

MinConNLP.WorkingSetSingularException - exception com.imsl.math.MinConNLP.WorkingSetSingularException.

Working set is singular in dual extended QP.

MinConNLP.WorkingSetSingularException(String) - Constructor for class com.imsl.math.MinConNLP.WorkingSetSingularException

MinConNLP.WorkingSetSingularException(String, Object[]) - Constructor for class com.imsl.math.MinConNLP.WorkingSetSingularException

MinUncon - class com.imsl.math.MinUncon.

Unconstrained minimization.

MinUncon() - Constructor for class com.imsl.math.MinUncon

Unconstrained minimum constructor for a smooth function of a single variable of type double.

MinUncon.Derivative - interface com.imsl.math.MinUncon.Derivative.

Public interface for the user supplied function to the MinUncon object.

MinUncon.Function - interface com.imsl.math.MinUncon.Function.

Public interface for the user supplied function to the MinUncon object.

MinUnconMultiVar - class com.imsl.math.MinUnconMultiVar.

Unconstrained multivariate minimization.

MinUnconMultiVar(int) - Constructor for class com.imsl.math.MinUnconMultiVar

Unconstrained minimum constructor for a function of n variables of type double.

MinUnconMultiVar.ApproximateMinimumException - exception com.imsl.math.MinUnconMultiVar.ApproximateMinimumException.

Scaled step tolerance satisfied; the current point may be an approximate local solution, or the algorithm is making very slow progress and is not near a solution, or the scaled step tolerance is too big.

MinUnconMultiVar.ApproximateMinimumException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.ApproximateMinimumException

MinUnconMultiVar.ApproximateMinimumException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.ApproximateMinimumException

MinUnconMultiVar.FalseConvergenceException - exception com.imsl.math.MinUnconMultiVar.FalseConvergenceException.

False convergence error; the iterates appear to be converging to a noncritical point.

MinUnconMultiVar.FalseConvergenceException(String) - Constructor for class com.imsl.math.MinUnconMultiVar.FalseConvergenceException

MinUnconMultiVar.FalseConvergenceException(String, Object[]) - Constructor for class com.imsl.math.MinUnconMultiVar.FalseConvergenceException

Min