Index (numerics4j 1.3 API)

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A B C D E F G H I L M N P R S T U W

A

AbstractContinuousRandomVariable - Class in net.sf.doodleproject.numerics4j.random: Base continuous random variable that provides a {@link RNG) instance as a source for uniform random numbers.
AbstractContinuousRandomVariable(RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.AbstractContinuousRandomVariable: Create a random variable with the given source generator.
AbstractDiscreteRandomVariable - Class in net.sf.doodleproject.numerics4j.random: Base continuous random variable that provides a {@link RNG) instance as a source for uniform random numbers.
AbstractDiscreteRandomVariable(RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.AbstractDiscreteRandomVariable: Create a random variable with the given source generator.
acosh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the inverse hyperbolic cosine of x.
AdaptiveIntegrator - Class in net.sf.doodleproject.numerics4j.integration: An implementation of adaptive quadrature.
AdaptiveIntegrator(Function) - Constructor for class net.sf.doodleproject.numerics4j.integration.AdaptiveIntegrator: Create an integrator for the given function.
AdaptiveIntegrator(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.integration.AdaptiveIntegrator: Create an integrator for the given function.
add(double) - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Adds an element to the end of this expandable array.
asinh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the inverse hyperbolic sine of x.
atanh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the inverse hyperbolic tangent of x.

B

BernoulliRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Bernoulli distribution.
BernoulliRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.BernoulliRandomVariable: Default constructor.
BernoulliRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.BernoulliRandomVariable: Create a random variable with the given probability of success.
BernoulliRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.BernoulliRandomVariable: Create a random variable with the given probability of success and source generator.
Beta - Class in net.sf.doodleproject.numerics4j.special: Utility class that provides methods related to the beta family of functions.
BetaDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Beta distribution (1).
BetaDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Default constructor.
BetaDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Create a distribution with the given alpha and beta values.
BetaRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Beta distribution.
BetaRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.BetaRandomVariable: Default constructor.
BetaRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.BetaRandomVariable: Create a random variable with the given alpha and beta values.
BetaRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.BetaRandomVariable: Create a random variable with the given parameters.
BinomialDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Binomial distribution.
BinomialDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Default constructor.
BinomialDistribution(int, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Create a distribution with the given number of trials and probability of success.
BinomialRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Binomial distribution.
BinomialRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.BinomialRandomVariable: Default constructor.
BinomialRandomVariable(int, double) - Constructor for class net.sf.doodleproject.numerics4j.random.BinomialRandomVariable: Create a random variable with the given number of trials and probability of success.
BinomialRandomVariable(int, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.BinomialRandomVariable: Create a random variable with the given parameters.
BisectionRootFinder - Class in net.sf.doodleproject.numerics4j.root: The bisection method (1) for finding roots of functions.
BisectionRootFinder(Function) - Constructor for class net.sf.doodleproject.numerics4j.root.BisectionRootFinder: Create a root finder for the given function.
BisectionRootFinder(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.root.BisectionRootFinder: Create a root finder for the given function.
Bracket - Class in net.sf.doodleproject.numerics4j.root: Simple root bracketing routine.
Bracket(Function) - Constructor for class net.sf.doodleproject.numerics4j.root.Bracket: Create a root bracketer for the given function.
Bracket(Function, int) - Constructor for class net.sf.doodleproject.numerics4j.root.Bracket: Create a root bracketer for the given function.
bracketOut(double, double, double) - Method in class net.sf.doodleproject.numerics4j.root.Bracket: Bracket a root for the target function by creating and continuously expanding an interval around the initial point until the interval is known to contain at least one root.
BrentRootFinder - Class in net.sf.doodleproject.numerics4j.root: Brent's method (1) for finding roots of functions.
BrentRootFinder(Function) - Constructor for class net.sf.doodleproject.numerics4j.root.BrentRootFinder: Create a root finder for the given function.
BrentRootFinder(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.root.BrentRootFinder: Create a root finder for the given function.

C

CauchyDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Cauchy distribution (1).
CauchyDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Default constructor.
CauchyDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Create a distribution with the given location and scale parameters.
CauchyRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Cauchy distribution.
CauchyRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.CauchyRandomVariable: Default constructor.
CauchyRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.CauchyRandomVariable: Create a random variable with the given location and scale parameters.
CauchyRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.CauchyRandomVariable: Create a random variable with the given parameters.
ChiSquaredDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Chi-Squared distribution (1).
ChiSquaredDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: Default constructor.
ChiSquaredDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: Create a distribution with the given degrees of freedom.
ChiSquaredRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Chi-Squared distribution.
ChiSquaredRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.ChiSquaredRandomVariable: Default constructor.
ChiSquaredRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.ChiSquaredRandomVariable: Create a random variable with the given degrees of freedom.
ChiSquaredRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.ChiSquaredRandomVariable: Create a random variable with the given parameters.
clear() - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Remove all elements from this collection.
Constants - Interface in net.sf.doodleproject.numerics4j: Common constants found in mathematical formulas.
ContinuedFraction - Class in net.sf.doodleproject.numerics4j.continuedfraction: This class provides the means to evaluate continued fractions (1).
ContinuedFraction() - Constructor for class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction: Default constructor.
ContinuedFraction(int, double) - Constructor for class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction: Create a continued fraction with the given number of maximum iterations and maximum relative error.
ContinuedFraction.IterativeState - Class in net.sf.doodleproject.numerics4j.continuedfraction: The internal state used during continued fraction evaluation.
ContinuedFraction.IterativeState(double) - Constructor for class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Create a state object for the given evaluation point.
ContinuousDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: Base continuous distribution.
ContinuousDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.ContinuousDistribution
ContinuousRandomVariable - Interface in net.sf.doodleproject.numerics4j.random: A random variable generator for a continuous distribution.
ConvergenceException - Exception in net.sf.doodleproject.numerics4j.exception: The exception raised when an iterative method fails to converge.
ConvergenceException(String) - Constructor for exception net.sf.doodleproject.numerics4j.exception.ConvergenceException: Create an execption with the given message.
cosh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the hyperbolic cosine of x.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ContinuousDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: The CDF for this distribution.
cumulativeProbability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: The CDF for this distribution.
cumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: The CDF for this distribution.

D

DiscreteDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: Base discrete distribution.
DiscreteDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution
DiscreteRandomVariable - Interface in net.sf.doodleproject.numerics4j.random: A random variable generator for a discrete distribution.
Distribution - Interface in net.sf.doodleproject.numerics4j.statistics.distribution: Base statistical distribution.
DoubleArray - Class in net.sf.doodleproject.numerics4j.util: An expandable double array.
DoubleArray() - Constructor for class net.sf.doodleproject.numerics4j.util.DoubleArray

E

Erf - Class in net.sf.doodleproject.numerics4j.special: Utility class that provides methods related to the error function.
erf(double) - Static method in class net.sf.doodleproject.numerics4j.special.Erf: Returns the error function erf(x) (1).
erfc(double) - Static method in class net.sf.doodleproject.numerics4j.special.Erf: Returns the complementary error function erfc(x) (1).
evaluate(double) - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction: Evaluate this continued fraction at the given value.
evaluate(double) - Method in interface net.sf.doodleproject.numerics4j.function.Function: Evaluate this function, f, at the domain value x.
evaluate(double) - Method in class net.sf.doodleproject.numerics4j.series.PowerSeries: Evaluate this series at the given value.
evaluate(double) - Method in class net.sf.doodleproject.numerics4j.series.Series: Evaluate this series at the given value.
ExponentialDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Exponential distribution (1).
ExponentialDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: Default constructor.
ExponentialDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: Create a distribution with the given mean.
ExponentialRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Exponential distribution.
ExponentialRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.ExponentialRandomVariable: Default constructor.
ExponentialRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.ExponentialRandomVariable: Create a random variable with the given mean.
ExponentialRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.ExponentialRandomVariable: Create a random variable with the given parameters.

F

FalsePositionRootFinder - Class in net.sf.doodleproject.numerics4j.root: The false position method (1) for finding roots of functions.
FalsePositionRootFinder(Function) - Constructor for class net.sf.doodleproject.numerics4j.root.FalsePositionRootFinder: Create a root finder for the given function.
FalsePositionRootFinder(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.root.FalsePositionRootFinder: Create a root finder for the given function.
FDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The F distribution (1).
FDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Default constructor.
FDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Create a distribution with the given numerator degrees of freedom and denominator degrees of freedom.
findInverseCumulativeProbability(double, double, double, double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ContinuousDistribution: Generic means to compute inverse cumulative probability values.
findInverseCumulativeProbability(double, int, int, int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution: Generic means to compute inverse cumulative probability values.
findRoot(double, double) - Method in class net.sf.doodleproject.numerics4j.root.BisectionRootFinder: Find a root of the target function that lies in the interval [ min, max].
findRoot(double, double) - Method in class net.sf.doodleproject.numerics4j.root.BrentRootFinder: Find a root of the target function that lies between the two initial approximations, x0 and x1.
findRoot(double, double) - Method in class net.sf.doodleproject.numerics4j.root.FalsePositionRootFinder: Find a root of the target function that lies in the interval [ min, max].
findRoot(double) - Method in class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Find a root of the target function that lies close to x.
findRoot(double, double) - Method in class net.sf.doodleproject.numerics4j.root.SecantRootFinder: Find a root of the target function that lies around the two initial approximations, x0 and x1.
FRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the F distribution.
FRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.FRandomVariable: Default constructor.
FRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.FRandomVariable: Create a random variable with the given numerator degrees of freedom and denominator degrees of freedom.
FRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.FRandomVariable: Create a random variable with the given parameters.
Function - Interface in net.sf.doodleproject.numerics4j.function: A single variable function.

G

Gamma - Class in net.sf.doodleproject.numerics4j.special: Utility class that provides methods related to the gamma family of functions.
GammaDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Gamma distribution (1).
GammaDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Default constructor.
GammaDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Create a distribution with the given alpha and beta values.
GammaRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Gamma distribution.
GammaRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.GammaRandomVariable: Default constructor.
GammaRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.GammaRandomVariable: Create a random variable with the given alpha and beta values.
GammaRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.GammaRandomVariable: Create a random variable with the given parameters.
GeometricDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Geometric distribution.
GeometricDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: Default constructor.
GeometricDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: Create a distribution with the given probability of success.
GeometricRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Geometric distribution.
GeometricRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.GeometricRandomVariable: Default constructor.
GeometricRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.GeometricRandomVariable: Create a random variable with the given probability of success.
GeometricRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.GeometricRandomVariable: Create a random variable with the given parameters.
get(int) - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Access the element at the given index.
getA(int, double) - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction: Access the n-th a coefficient.
getAlpha() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Access the alpha parameter.
getAlpha() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Access the alpha parameter.
getB(int, double) - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction: Access the n-th b coefficient.
getBeta() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Access the beta parameter.
getBeta() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Access the beta parameter.
getDegreesOfFreedom() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: Access the degrees of freedom.
getDegreesOfFreedom() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: Access the degrees of freedom.
getDenominatorDegreesOfFreedom() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Access the denominator degrees of freedom.
getDerivative() - Method in class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Access the derivative of the target function.
getDeviancePart(double, double) - Static method in class net.sf.doodleproject.numerics4j.statistics.distribution.SaddlePointExpansion: A part of the deviance portion of the saddle point approximation.
getFunction() - Method in class net.sf.doodleproject.numerics4j.integration.AdaptiveIntegrator: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.integration.RombergIntegrator: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.integration.SimpsonsIntegrator: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.BisectionRootFinder: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.Bracket: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.BrentRootFinder: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.FalsePositionRootFinder: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Access the target function.
getFunction() - Method in class net.sf.doodleproject.numerics4j.root.SecantRootFinder: Access the target function.
getIterations() - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Access the current iteration.
getIterations() - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator.IterativeState: Access the current iteration.
getIterations() - Method in interface net.sf.doodleproject.numerics4j.IterativeMethod.IterativeState: Access the current iteration.
getIterations() - Method in class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Access the current iteration.
getLocation() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Access the location parameter.
getLower() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Access the lower parameter.
getMaximumIterations() - Method in class net.sf.doodleproject.numerics4j.IterativeMethod: Access the maximum number of iterations.
getMaximumIterations() - Method in class net.sf.doodleproject.numerics4j.root.Bracket: Access the maximum number of iterations.
getMaximumRelativeError() - Method in class net.sf.doodleproject.numerics4j.IterativeMethod: Access the maximum relative error.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: Access the mean.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Access the mean.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Access the mean.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Access the mean.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Access the mean.
getMean() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: Access the mean.
getMedian() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Access the location parameter.
getNumberOfFailures() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Access the number of failures.
getNumberOfSuccesses() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Access the number of successes.
getNumberOfSuccesses() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Access the number of successes.
getNumberOfTrials() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Access the number of trials.
getNumeratorDegreesOfFreedom() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Access the numerator degrees of freedom.
getProbabilityOfSuccess() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Access probability of success.
getProbabilityOfSuccess() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: Access probability of success.
getProbabilityOfSuccess() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Access probability of success.
getRelativeError() - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Access the current relative error in the evaluation.
getRelativeError() - Method in interface net.sf.doodleproject.numerics4j.IterativeMethod.IterativeState: Access the current relative error in the evaluation.
getRelativeError() - Method in class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Access the current relative error in the evaluation.
getResult() - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Access the result of this evaluation.
getResult() - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator.IterativeState: Access the result of this root finding.
getResult() - Method in class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Access the result of this evaluation.
getSampleSize() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Access the sample size.
getScale() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Access the scale parameter.
getScale() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Access the scale.
getScale() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Access the scale parameter.
getScale() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: Access the scale parameter.
getScale() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Access the scale parameter.
getShape() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Access the shape parameter.
getSize() - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Access the size of this array.
getSource() - Method in class net.sf.doodleproject.numerics4j.random.AbstractContinuousRandomVariable: Access the source generator.
getSource() - Method in class net.sf.doodleproject.numerics4j.random.AbstractDiscreteRandomVariable: Access the source generator.
getStandardDeviation() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Access the standard deviation.
getStandardDeviation() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Access the standard deviation.
getStirlingError(double) - Static method in class net.sf.doodleproject.numerics4j.statistics.distribution.SaddlePointExpansion: Compute the error of Stirling's series at the given value.
getTerm(int) - Method in class net.sf.doodleproject.numerics4j.series.PowerSeries: Access the n-th term for this series.
getTerm(int, double) - Method in class net.sf.doodleproject.numerics4j.series.Series: Access the n-th term for this series.
getUpper() - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Access the upper parameter.

H

HALF_LOG_2_PI - Static variable in interface net.sf.doodleproject.numerics4j.Constants: 1/2 * log(2 π).
HypergeometricDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Hypergeometric distribution.
HypergeometricDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Default constructor.
HypergeometricDistribution(int, int, int) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Create a distribution with the given number of failures, number of successes, and sample size.

I

initialize() - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Initialize the state to begin a continued fraction evaluation.
initialize() - Method in interface net.sf.doodleproject.numerics4j.IterativeMethod.IterativeState: Initialize the state to begin an iterative evaluation.
initialize() - Method in class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Initialize the state to begin a series evaluation.
integrate(double, double) - Method in class net.sf.doodleproject.numerics4j.integration.AdaptiveIntegrator: Evaluate the definite integral from a to b.
integrate(double, double) - Method in class net.sf.doodleproject.numerics4j.integration.RombergIntegrator: Evaluate the definite integral from a to b.
integrate(double, double) - Method in class net.sf.doodleproject.numerics4j.integration.SimpsonsIntegrator: Evaluate the definite integral from a to b.
integrate(double, double) - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator: Evaluate the definite integral from a to b.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ContinuousDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: The inverse CDF for this distribution.
inverseCumulativeProbability(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: The inverse CDF for this distribution.
inverseErf(double) - Static method in class net.sf.doodleproject.numerics4j.special.Erf: Returns the inverse error function erf^-1(y).
iterate() - Method in class net.sf.doodleproject.numerics4j.continuedfraction.ContinuedFraction.IterativeState: Perform the next iteration of the continued fraction evaluation.
iterate() - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator.IterativeState: Perform the next iteration of finding a root.
iterate(IterativeMethod.IterativeState) - Method in class net.sf.doodleproject.numerics4j.IterativeMethod: Perform the iterative evaluation.
iterate() - Method in interface net.sf.doodleproject.numerics4j.IterativeMethod.IterativeState: Perform the next iteration of the iterative evaluation.
iterate() - Method in class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Perform the next iteration of the series evaluation.
IterativeMethod - Class in net.sf.doodleproject.numerics4j: A method to solve generic problems by finding successive (and hopefully better) approximations to the solution.
IterativeMethod() - Constructor for class net.sf.doodleproject.numerics4j.IterativeMethod: Default constructor.
IterativeMethod(int, double) - Constructor for class net.sf.doodleproject.numerics4j.IterativeMethod: Create an iterative method with the given number of maximum iterations and maximum relative error.
IterativeMethod.IterativeState - Interface in net.sf.doodleproject.numerics4j: The current state for an iterative method.

L

LaplaceDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Laplace distribution.
LaplaceDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Default constructor.
LaplaceDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Create a distribution with the given mean and scale.
LaplaceRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Laplace distribution.
LaplaceRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.LaplaceRandomVariable: Default constructor.
LaplaceRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.LaplaceRandomVariable: Create a random variable with the given mean and scale.
LaplaceRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.LaplaceRandomVariable: Create a random variable with the given parameters.
LinearCongruentialRNG - Class in net.sf.doodleproject.numerics4j.random: A general linear congruential generator.
LinearCongruentialRNG(long, long) - Constructor for class net.sf.doodleproject.numerics4j.random.LinearCongruentialRNG: Create a linear congruential generator with the given modulus and multiplier.
LinearCongruentialRNG(long, long, long) - Constructor for class net.sf.doodleproject.numerics4j.random.LinearCongruentialRNG: Create a linear congruential generator with the given parameters.
LinearCongruentialRNG(long, long, long, long) - Constructor for class net.sf.doodleproject.numerics4j.random.LinearCongruentialRNG: Create a linear congruential generator with the given parameters.
LOG_2_PI - Static variable in interface net.sf.doodleproject.numerics4j.Constants: log(2 π).
logBeta(double, double) - Static method in class net.sf.doodleproject.numerics4j.special.Beta: Returns the natural logarithm of the beta function B(a, b) (1).
logBinomialProbability(int, int, double, double) - Static method in class net.sf.doodleproject.numerics4j.statistics.distribution.SaddlePointExpansion: Compute the PMF for a binomial distribution using the saddle point expansion.
logGamma(double) - Static method in class net.sf.doodleproject.numerics4j.special.Gamma: Returns the natural logarithm of the gamma function Γ(x) (1).
LogisticDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Logistic distribution.
LogisticDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Default constructor.
LogisticDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Create a distribution with the given mean and scale parameters.
LogisticRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Logistic distribution.
LogisticRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.LogisticRandomVariable: Default constructor.
LogisticRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.LogisticRandomVariable: Create a random variable with the given mean and scale.
LogisticRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.LogisticRandomVariable: Create a random variable with the given parameters.
LogNormalDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Log Normal distribution.
LogNormalDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Default constructor.
LogNormalDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Create a distribution with the given mean and standard deviation.
LogNormalRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Log Normal distribution.
LogNormalRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.LogNormalRandomVariable: Default constructor.
LogNormalRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.LogNormalRandomVariable: Create a random variable with the given mean and standard deviation.
LogNormalRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.LogNormalRandomVariable: Create a random variable with the given parameters.

M

MathRNG - Class in net.sf.doodleproject.numerics4j.random: A random number generator that delegates random number generation to the Math.random() method.
MathRNG() - Constructor for class net.sf.doodleproject.numerics4j.random.MathRNG

N

NegativeBinomialDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Negative Binomial distribution.
NegativeBinomialDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Default constructor.
NegativeBinomialDistribution(int, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Create a distribution with the given number of successes and probability of success.
NegativeBinomialRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Negative Binomial distribution.
NegativeBinomialRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.NegativeBinomialRandomVariable: Default constructor.
NegativeBinomialRandomVariable(int, double) - Constructor for class net.sf.doodleproject.numerics4j.random.NegativeBinomialRandomVariable: Create a random variable with the given number of successes and probability of success.
NegativeBinomialRandomVariable(int, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.NegativeBinomialRandomVariable: Create a random variable with the given parameters.
net.sf.doodleproject.numerics4j - package net.sf.doodleproject.numerics4j: Common classes used throughout numerics4j.
net.sf.doodleproject.numerics4j.continuedfraction - package net.sf.doodleproject.numerics4j.continuedfraction: A continued fraction evaluator.
net.sf.doodleproject.numerics4j.exception - package net.sf.doodleproject.numerics4j.exception: Exceptions raised throughout numerics4j.
net.sf.doodleproject.numerics4j.function - package net.sf.doodleproject.numerics4j.function: Root finding routines.
net.sf.doodleproject.numerics4j.integration - package net.sf.doodleproject.numerics4j.integration: Function interfaces.
net.sf.doodleproject.numerics4j.random - package net.sf.doodleproject.numerics4j.random: Random number generators and random variable generators.
net.sf.doodleproject.numerics4j.root - package net.sf.doodleproject.numerics4j.root: Function interfaces.
net.sf.doodleproject.numerics4j.series - package net.sf.doodleproject.numerics4j.series: Evaluation of infinite series.
net.sf.doodleproject.numerics4j.special - package net.sf.doodleproject.numerics4j.special: Elementary functions not provided by the Java™.
net.sf.doodleproject.numerics4j.statistics.distribution - package net.sf.doodleproject.numerics4j.statistics.distribution: Statistical distributions.
net.sf.doodleproject.numerics4j.util - package net.sf.doodleproject.numerics4j.util: Utility classes used by numerics4j.
NewtonRootFinder - Class in net.sf.doodleproject.numerics4j.root: Newton's method (1) for finding roots of functions.
NewtonRootFinder(Function, Function) - Constructor for class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Create a root finder for the given function.
NewtonRootFinder(Function, Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Create a root finder for the given function.
nextRandomNumber() - Method in class net.sf.doodleproject.numerics4j.random.AbstractContinuousRandomVariable: Access the next random number from the source generator.
nextRandomNumber() - Method in class net.sf.doodleproject.numerics4j.random.AbstractDiscreteRandomVariable: Access the next random number from the source generator.
nextRandomNumber() - Method in class net.sf.doodleproject.numerics4j.random.LinearCongruentialRNG: Access the next random number from this generator.
nextRandomNumber() - Method in class net.sf.doodleproject.numerics4j.random.MathRNG: Access the next random number from this generator.
nextRandomNumber() - Method in class net.sf.doodleproject.numerics4j.random.RandomRNG: Access the next random number from this generator.
nextRandomNumber() - Method in interface net.sf.doodleproject.numerics4j.random.RNG: Access the next random number from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.BernoulliRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.BernoulliRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.BetaRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.BetaRandomVariable: Access the next random variable from this generator.
nextRandomVariable(int, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.BinomialRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.BinomialRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.CauchyRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.CauchyRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.ChiSquaredRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.ChiSquaredRandomVariable: Access the next random variable from this generator.
nextRandomVariable() - Method in interface net.sf.doodleproject.numerics4j.random.ContinuousRandomVariable: Access the next random variable from this generator.
nextRandomVariable() - Method in interface net.sf.doodleproject.numerics4j.random.DiscreteRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.ExponentialRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.ExponentialRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.FRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.FRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.GammaRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.GammaRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.GeometricRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.GeometricRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.LaplaceRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.LaplaceRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.LogisticRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.LogisticRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.LogNormalRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.LogNormalRandomVariable: Access the next random variable from this generator.
nextRandomVariable(int, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.NegativeBinomialRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.NegativeBinomialRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.NormalRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.NormalRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.PoissonRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.PoissonRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.RayleighRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.RayleighRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.TRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.TRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.UniformRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.UniformRandomVariable: Access the next random variable from this generator.
nextRandomVariable(double, double, double, RNG) - Static method in class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Access the next random variable using the given generator.
nextRandomVariable() - Method in class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Access the next random variable from this generator.
NormalDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Normal distribution (1).
NormalDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Default constructor.
NormalDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Create a distribution with the given mean and standard deviation.
NormalRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Normal distribution.
NormalRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.NormalRandomVariable: Default constructor.
NormalRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.NormalRandomVariable: Create a random variable with the given mean and standard deviation.
NormalRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.NormalRandomVariable: Create a random variable with the given parameters.
NumericException - Exception in net.sf.doodleproject.numerics4j.exception: Generic numerical exception thrown by numerics4j.
NumericException(String) - Constructor for exception net.sf.doodleproject.numerics4j.exception.NumericException: Create an execption with the given message.

P

PI_2 - Static variable in interface net.sf.doodleproject.numerics4j.Constants: 2 π.
PoissonDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Poisson distribution.
PoissonDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: Default distribution.
PoissonDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: Create a distribution with the given mean.
PoissonRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Poisson distribution.
PoissonRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.PoissonRandomVariable: Default constructor.
PoissonRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.PoissonRandomVariable: Create a random variable with the given mean.
PoissonRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.PoissonRandomVariable: Create a random variable with the given parameters.
PowerSeries - Class in net.sf.doodleproject.numerics4j.series: This class provides the means to evaluate infinite power series (1).
PowerSeries() - Constructor for class net.sf.doodleproject.numerics4j.series.PowerSeries: Default constructor.
PowerSeries(int, double) - Constructor for class net.sf.doodleproject.numerics4j.series.PowerSeries: Create a series with the given number of maximum iterations and maximum relative error.
PowerSeries(int, int, double) - Constructor for class net.sf.doodleproject.numerics4j.series.PowerSeries: Create a series with the given first term index, number of maximum iterations and maximum relative error.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: The PMF for this distribution.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution: The PMF for this distribution.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: The PMF for this distribution.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: The PMF for this distribution.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: The PMF for this distribution.
probability(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: The PMF for this distribution.

R

RandomRNG - Class in net.sf.doodleproject.numerics4j.random: A random number generator that delegates random number generation to a Random object.
RandomRNG() - Constructor for class net.sf.doodleproject.numerics4j.random.RandomRNG: Create a random number generator using a default Random delegate.
RandomRNG(long) - Constructor for class net.sf.doodleproject.numerics4j.random.RandomRNG: Create a random number generator using a Random delegate initialized with the given seed.
RandomRNG(Random) - Constructor for class net.sf.doodleproject.numerics4j.random.RandomRNG: Create a random number generator using the given Random delegate.
RayleighDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Rayleigh distribution.
RayleighDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: Default constructor.
RayleighDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: Create a distribution with the scale parameter.
RayleighRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Rayleigh distribution.
RayleighRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.RayleighRandomVariable: Default constructor.
RayleighRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.RayleighRandomVariable: Create a random variable with the given mean.
RayleighRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.RayleighRandomVariable: Create a random variable with the given parameters.
regularizedBeta(double, double, double) - Static method in class net.sf.doodleproject.numerics4j.special.Beta: Returns the regularized beta function I_x(a, b) (1).
regularizedGammaP(double, double) - Static method in class net.sf.doodleproject.numerics4j.special.Gamma: Returns the regularized gamma function P(a, x) (1).
regularizedGammaQ(double, double) - Static method in class net.sf.doodleproject.numerics4j.special.Gamma: Returns the regularized gamma function Q(a, x) = 1 - P(a, x) (1).
RNG - Interface in net.sf.doodleproject.numerics4j.random: Defines a random number generator that is capable of generating sequences of random numbers uniformly distributed between zero and one.
RombergIntegrator - Class in net.sf.doodleproject.numerics4j.integration: An implementation of Romberg Integration.
RombergIntegrator(Function) - Constructor for class net.sf.doodleproject.numerics4j.integration.RombergIntegrator: Create an integrator for the given function.
RombergIntegrator(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.integration.RombergIntegrator: Create an integrator for the given function.

S

SaddlePointExpansion - Class in net.sf.doodleproject.numerics4j.statistics.distribution: Utility class used by various distributions to accurately compute their respective probability mass functions.
SecantRootFinder - Class in net.sf.doodleproject.numerics4j.root: The secant method (1) for finding roots of functions.
SecantRootFinder(Function) - Constructor for class net.sf.doodleproject.numerics4j.root.SecantRootFinder: Create a root finder for the given function.
SecantRootFinder(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.root.SecantRootFinder: Create a root finder for the given function.
Series - Class in net.sf.doodleproject.numerics4j.series: This class provides the means to evaluate infinite series (1).
Series() - Constructor for class net.sf.doodleproject.numerics4j.series.Series: Default constructor.
Series(int, double) - Constructor for class net.sf.doodleproject.numerics4j.series.Series: Create a series with the given number of maximum iterations and maximum relative error.
Series(int, int, double) - Constructor for class net.sf.doodleproject.numerics4j.series.Series: Create a series with the given first term index, number of maximum iterations and maximum relative error.
Series.IterativeState - Class in net.sf.doodleproject.numerics4j.series: The internal state used during series evaluation.
Series.IterativeState(double) - Constructor for class net.sf.doodleproject.numerics4j.series.Series.IterativeState: Create a state object for the given evaluation point.
set(int, double) - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Modify the element at the given index.
setAlpha(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Modify the alpha parameter.
setAlpha(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Modify the alpha parameter.
setBeta(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BetaDistribution: Modify the beta parameter.
setBeta(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GammaDistribution: Modify the beta parameter.
setDegreesOfFreedom(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ChiSquaredDistribution: Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: Modify the degrees of freedom.
setDenominatorDegreesOfFreedom(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Modify the denominator degrees of freedom.
setDerivative(Function) - Method in class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Modify the derivative of the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.integration.AdaptiveIntegrator: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.integration.RombergIntegrator: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.integration.SimpsonsIntegrator: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.BisectionRootFinder: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.Bracket: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.BrentRootFinder: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.FalsePositionRootFinder: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.NewtonRootFinder: Modify the target function.
setFunction(Function) - Method in class net.sf.doodleproject.numerics4j.root.SecantRootFinder: Modify the target function.
setLocation(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Modify the location parameter.
setLower(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Modify the lower bound parameter.
setMaximumIterations(int) - Method in class net.sf.doodleproject.numerics4j.IterativeMethod: Modify the maximum number of iterations.
setMaximumIterations(int) - Method in class net.sf.doodleproject.numerics4j.root.Bracket: Modify the maximum number of iterations.
setMaximumRelativeError(double) - Method in class net.sf.doodleproject.numerics4j.IterativeMethod: Modify the maximum relative error.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.ExponentialDistribution: Modify the mean.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Modify the mean.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Modify the mean.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Modify the mean.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Modify the mean.
setMean(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.PoissonDistribution: Modify the mean.
setMedian(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Modify the location parameter.
setNumberOfFailures(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Modify the number of failures.
setNumberOfSuccesses(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Modify the number of successes.
setNumberOfSuccesses(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Modify the number of successes.
setNumberOfTrials(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Modify the number of trials.
setNumeratorDegreesOfFreedom(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.FDistribution: Modify the numerator degrees of freedom.
setProbabilityOfSuccess(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.BinomialDistribution: Modify probability of success.
setProbabilityOfSuccess(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.GeometricDistribution: Modify probability of success.
setProbabilityOfSuccess(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NegativeBinomialDistribution: Modify probability of success.
setSampleSize(int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.HypergeometricDistribution: Modify the sample size.
setScale(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.CauchyDistribution: Modify the scale parameter.
setScale(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LaplaceDistribution: Modify the scale.
setScale(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogisticDistribution: Modify the scale parameter.
setScale(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.RayleighDistribution: Modify the scale parameter.
setScale(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Modify the scale parameter.
setShape(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Modify the shape parameter.
setSize(int) - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Modify the size of this array.
setStandardDeviation(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.LogNormalDistribution: Modify the standard deviation.
setStandardDeviation(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.NormalDistribution: Modify the standard deviation.
setUpper(double) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Modify the upper bound parameter.
simpleCumulativeProbability(int, int) - Method in class net.sf.doodleproject.numerics4j.statistics.distribution.DiscreteDistribution: Generic means to compute cumulative probability values.
SimpsonsIntegrator - Class in net.sf.doodleproject.numerics4j.integration: The extended Simpson's rule for numerically integrating functions.
SimpsonsIntegrator(Function) - Constructor for class net.sf.doodleproject.numerics4j.integration.SimpsonsIntegrator: Create an integrator for the given function.
SimpsonsIntegrator(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.integration.SimpsonsIntegrator: Create an integrator for the given function.
sinh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the hyperbolic sine of x.
SQRT_2 - Static variable in interface net.sf.doodleproject.numerics4j.Constants: √2.

T

tanh(double) - Static method in class net.sf.doodleproject.numerics4j.special.Trigonometric: Returns the hyperbolic tangent of x.
TDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: Student's t distribution (1).
TDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: Default constructor.
TDistribution(double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.TDistribution: Create a distribution with the given degrees of freedom.
toArray() - Method in class net.sf.doodleproject.numerics4j.util.DoubleArray: Convert this array into a native array.
TRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for Student's t distribution.
TRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.TRandomVariable: Default constructor.
TRandomVariable(double) - Constructor for class net.sf.doodleproject.numerics4j.random.TRandomVariable: Create a random variable with the given degrees of freedom.
TRandomVariable(double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.TRandomVariable: Create a random variable with the given parameters.
TrapezoidalIntegrator - Class in net.sf.doodleproject.numerics4j.integration: The extended trapezoidal rule for numerically integrating functions.
TrapezoidalIntegrator(Function) - Constructor for class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator: Create an integrator for the given function.
TrapezoidalIntegrator(Function, int, double) - Constructor for class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator: Create an integrator for the given function.
TrapezoidalIntegrator.IterativeState - Class in net.sf.doodleproject.numerics4j.integration: The internal state used during root finding.
TrapezoidalIntegrator.IterativeState(Function, double, double) - Constructor for class net.sf.doodleproject.numerics4j.integration.TrapezoidalIntegrator.IterativeState: Create a state object for the given initial root approximation.
Trigonometric - Class in net.sf.doodleproject.numerics4j.special: Utility class that provides methods related to the trigonometric functions.

U

UniformDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Uniform distribution (1).
UniformDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Default constructor.
UniformDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.UniformDistribution: Create a distribution with the given lower bound and upper bound values.
UniformRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Uniform distribution.
UniformRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.UniformRandomVariable: Default constructor.
UniformRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.UniformRandomVariable: Create a random variable with the given lower bound and upper bound values.
UniformRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.UniformRandomVariable: Create a random variable with the given parameters.

W

WeibullDistribution - Class in net.sf.doodleproject.numerics4j.statistics.distribution: The Weibull distribution.
WeibullDistribution() - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Default constructor.
WeibullDistribution(double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Create a distribution with the given parameters.
WeibullDistribution(double, double, double) - Constructor for class net.sf.doodleproject.numerics4j.statistics.distribution.WeibullDistribution: Create a distribution with the given parameters.
WeibullRandomVariable - Class in net.sf.doodleproject.numerics4j.random: A random variable generator for the Weibull distribution.
WeibullRandomVariable() - Constructor for class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Default constructor.
WeibullRandomVariable(double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Create a rnadom variable with the given shape and scale values.
WeibullRandomVariable(double, double, double) - Constructor for class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Create a random variable with the given parameters.
WeibullRandomVariable(double, double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Create a random variable with the given parameters.
WeibullRandomVariable(double, double, RNG) - Constructor for class net.sf.doodleproject.numerics4j.random.WeibullRandomVariable: Create a random variable with the given shape and scale values.

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