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## Uses of Class
org.apache.commons.math3.exception.NumberIsTooSmallException

Packages that use NumberIsTooSmallException
org.apache.commons.math3.analysis.differentiation | This package holds the main interfaces and basic building block classes dealing with differentiation.
org.apache.commons.math3.analysis.integration | Numerical integration (quadrature) algorithms for univariate real functions.
org.apache.commons.math3.analysis.interpolation | Univariate real functions interpolation algorithms.
org.apache.commons.math3.analysis.solvers | Root finding algorithms, for univariate real functions.
org.apache.commons.math3.dfp | Decimal floating point library for Java
org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
org.apache.commons.math3.exception | Specialized exceptions for algorithms errors.
org.apache.commons.math3.genetics | This package provides Genetic Algorithms components and implementations.
org.apache.commons.math3.linear | Linear algebra support.
org.apache.commons.math3.ode | This package provides classes to solve Ordinary Differential Equations problems.
org.apache.commons.math3.ode.nonstiff | This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.apache.commons.math3.special | Implementations of special functions such as Beta and Gamma.
org.apache.commons.math3.stat | Data storage, manipulation and summary routines.
org.apache.commons.math3.stat.correlation | Correlations/Covariance computations.
org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction.
org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library.

Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.differentiation

Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooSmallException
`FiniteDifferencesDifferentiator(int nbPoints, double stepSize)` Build a differentiator with number of points and step size when independent variable is unbounded.
`FiniteDifferencesDifferentiator(int nbPoints, double stepSize, double tLower, double tUpper)` Build a differentiator with number of points and step size when independent variable is bounded.

Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.integration

Constructors in org.apache.commons.math3.analysis.integration that throw NumberIsTooSmallException
`BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given accuracies and iteration counts.
`BaseAbstractUnivariateIntegrator(int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given iteration counts.
`IterativeLegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Builds an integrator with given accuracies and iterations counts.
`LegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Deprecated. Build a Legendre-Gauss integrator with given accuracies and iterations counts.
`RombergIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a Romberg integrator with given accuracies and iterations counts.
`RombergIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a Romberg integrator with given iteration counts.
`SimpsonIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a Simpson integrator with given accuracies and iterations counts.
`SimpsonIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a Simpson integrator with given iteration counts.
`TrapezoidIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a trapezoid integrator with given accuracies and iterations counts.
`TrapezoidIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a trapezoid integrator with given iteration counts.

Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.interpolation

Methods in org.apache.commons.math3.analysis.interpolation that throw NumberIsTooSmallException
`protected static double[]` | `DividedDifferenceInterpolator.computeDividedDifference(double[] x, double[] y)` Return a copy of the divided difference array.
`PolynomialFunctionNewtonForm` | `DividedDifferenceInterpolator.interpolate(double[] x, double[] y)` Compute an interpolating function for the dataset.
`PolynomialSplineFunction` | `LoessInterpolator.interpolate(double[] xval, double[] yval)` Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a `SplineInterpolator` on the resulting fit.
`PolynomialSplineFunction` | `SplineInterpolator.interpolate(double[] x, double[] y)` Computes an interpolating function for the data set.
`UnivariateFunction` | `UnivariatePeriodicInterpolator.interpolate(double[] xval, double[] yval)` Compute an interpolating function for the dataset.
`PolynomialSplineFunction` | `LinearInterpolator.interpolate(double[] x, double[] y)` Computes a linear interpolating function for the data set.
`PolynomialFunctionLagrangeForm` | `NevilleInterpolator.interpolate(double[] x, double[] y)` Computes an interpolating function for the data set.
`double[]` | `LoessInterpolator.smooth(double[] xval, double[] yval)` Compute a loess fit on the data at the original abscissae.
`double[]` | `LoessInterpolator.smooth(double[] xval, double[] yval, double[] weights)` Compute a weighted loess fit on the data at the original abscissae.

Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.solvers

Constructors in org.apache.commons.math3.analysis.solvers that throw NumberIsTooSmallException
`BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, double functionValueAccuracy, int maximalOrder)` Construct a solver.
`BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, int maximalOrder)` Construct a solver.
`BracketingNthOrderBrentSolver(double absoluteAccuracy, int maximalOrder)` Construct a solver.

Uses of NumberIsTooSmallException in org.apache.commons.math3.dfp

Constructors in org.apache.commons.math3.dfp that throw NumberIsTooSmallException
`BracketingNthOrderBrentSolverDFP(Dfp relativeAccuracy, Dfp absoluteAccuracy, Dfp functionValueAccuracy, int maximalOrder)` Construct a solver.

Uses of NumberIsTooSmallException in org.apache.commons.math3.distribution

Constructors in org.apache.commons.math3.distribution that throw NumberIsTooSmallException
`TriangularDistribution(double a, double c, double b)` Creates a triangular real distribution using the given lower limit, upper limit, and mode.
`TriangularDistribution(RandomGenerator rng, double a, double c, double b)` Creates a triangular distribution.

Uses of NumberIsTooSmallException in org.apache.commons.math3.exception

Subclasses of NumberIsTooSmallException in org.apache.commons.math3.exception
`class` | `NotPositiveException` Exception to be thrown when the argument is negative.
`class` | `NotStrictlyPositiveException` Exception to be thrown when the argument is negative.

Uses of NumberIsTooSmallException in org.apache.commons.math3.genetics

Methods in org.apache.commons.math3.genetics that throw NumberIsTooSmallException
`void` | `ListPopulation.setPopulationLimit(int populationLimit)` Sets the maximal population size.

Constructors in org.apache.commons.math3.genetics that throw NumberIsTooSmallException
`FixedElapsedTime(long maxTime)` Create a new `FixedElapsedTime` instance.
`FixedElapsedTime(long maxTime, TimeUnit unit)` Create a new `FixedElapsedTime` instance.
`FixedGenerationCount(int maxGenerations)` Create a new FixedGenerationCount instance.

Uses of NumberIsTooSmallException in org.apache.commons.math3.linear

Subclasses of NumberIsTooSmallException in org.apache.commons.math3.linear
`class` | `NonPositiveDefiniteMatrixException` Exception to be thrown when a positive definite matrix is expected.

Methods in org.apache.commons.math3.linear that throw NumberIsTooSmallException
`protected void` | `RealVector.checkIndices(int start, int end)` Checks that the indices of a subvector are valid.
`static void` | `MatrixUtils.checkSubMatrixIndex(AnyMatrix m, int startRow, int endRow, int startColumn, int endColumn)` Check if submatrix ranges indices are valid.
`protected void` | `AbstractFieldMatrix.checkSubMatrixIndex(int startRow, int endRow, int startColumn, int endColumn)` Check if submatrix ranges indices are valid.
`void` | `AbstractRealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)` Copy a submatrix.
`void` | `RealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)` Copy a submatrix.
`void` | `FieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)` Copy a submatrix.
`void` | `AbstractFieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)` Copy a submatrix.
`RealMatrix` | `AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
`RealMatrix` | `RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
`FieldMatrix<T>` | `FieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
`BlockRealMatrix` | `BlockRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
`FieldMatrix<T>` | `AbstractFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
`FieldMatrix<T>` | `BlockFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
`T` | `FieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`T` | `Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`T` | `AbstractFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`T` | `FieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`T` | `Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`T` | `AbstractFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`double` | `Array2DRowRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`double` | `AbstractRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`double` | `RealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
`double` | `Array2DRowRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`double` | `AbstractRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`double` | `RealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
`double` | `ArrayRealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
`double` | `RealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
`double` | `ArrayRealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
`double` | `RealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
`T` | `FieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`T` | `AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`T` | `BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`T` | `FieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`T` | `AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`T` | `BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`double` | `AbstractRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`double` | `RealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`double` | `BlockRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
`double` | `AbstractRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`double` | `RealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`double` | `BlockRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
`double` | `ArrayRealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
`double` | `RealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
`double` | `ArrayRealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
`double` | `RealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
`T` | `FieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`T` | `Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`T` | `AbstractFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`T` | `BlockFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`T` | `FieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`T` | `Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`T` | `AbstractFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`T` | `BlockFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`double` | `Array2DRowRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`double` | `AbstractRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`double` | `RealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`double` | `BlockRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
`double` | `Array2DRowRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`double` | `AbstractRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`double` | `RealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
`double` | `BlockRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.

Uses of NumberIsTooSmallException in org.apache.commons.math3.ode

Methods in org.apache.commons.math3.ode that throw NumberIsTooSmallException
`abstract void` | `AbstractIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`double` | `AbstractIntegrator.integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)` Integrate the differential equations up to the given time.
`double` | `FirstOrderIntegrator.integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)` Integrate the differential equations up to the given time.
`protected void` | `AbstractIntegrator.sanityChecks(ExpandableStatefulODE equations, double t)` Check the integration span.
`protected void` | `MultistepIntegrator.start(double t0, double[] y0, double t)` Start the integration.

Constructors in org.apache.commons.math3.ode that throw NumberIsTooSmallException
`MultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build a multistep integrator with the given stepsize bounds.

Uses of NumberIsTooSmallException in org.apache.commons.math3.ode.nonstiff

Methods in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallException
`protected double` | `AdaptiveStepsizeIntegrator.filterStep(double h, boolean forward, boolean acceptSmall)` Filter the integration step.
`abstract void` | `AdamsIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`void` | `AdamsBashforthIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`abstract void` | `AdaptiveStepsizeIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`void` | `GraggBulirschStoerIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`void` | `EmbeddedRungeKuttaIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`void` | `AdamsMoultonIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`void` | `RungeKuttaIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
`protected void` | `AdaptiveStepsizeIntegrator.sanityChecks(ExpandableStatefulODE equations, double t)` Check the integration span.

Constructors in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallException
`AdamsBashforthIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Bashforth integrator with the given order and step control parameters.
`AdamsIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams integrator with the given order and step control parameters.
`AdamsMoultonIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Moulton integrator with the given order and error control parameters.

Uses of NumberIsTooSmallException in org.apache.commons.math3.special

Methods in org.apache.commons.math3.special that throw NumberIsTooSmallException
`static double` | `Gamma.logGamma1p(double x)` Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.

Uses of NumberIsTooSmallException in org.apache.commons.math3.stat

Methods in org.apache.commons.math3.stat that throw NumberIsTooSmallException
`static double` | `StatUtils.varianceDifference(double[] sample1, double[] sample2, double meanDifference)` Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).

Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.correlation

Methods in org.apache.commons.math3.stat.correlation that throw NumberIsTooSmallException
`double` | `StorelessCovariance.getCovariance(int xIndex, int yIndex)` Get the covariance for an individual element of the covariance matrix.
`RealMatrix` | `StorelessCovariance.getCovarianceMatrix()` Returns the covariance matrix
`double[][]` | `StorelessCovariance.getData()` Return the covariance matrix as two-dimensional array.

Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that throw NumberIsTooSmallException
`static double` | `TestUtils.homoscedasticT(double[] sample1, double[] sample2)`
`double` | `TTest.homoscedasticT(double[] sample1, double[] sample2)` Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
`static double` | `TestUtils.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double` | `TTest.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)` Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
`static double` | `TestUtils.homoscedasticTTest(double[] sample1, double[] sample2)`
`double` | `TTest.homoscedasticTTest(double[] sample1, double[] sample2)` Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
`static boolean` | `TestUtils.homoscedasticTTest(double[] sample1, double[] sample2, double alpha)`
`boolean` | `TTest.homoscedasticTTest(double[] sample1, double[] sample2, double alpha)` Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
`static double` | `TestUtils.homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double` | `TTest.homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)` Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
`static double` | `TestUtils.pairedT(double[] sample1, double[] sample2)`
`double` | `TTest.pairedT(double[] sample1, double[] sample2)` Computes a paired, 2-sample t-statistic based on the data in the input arrays.
`static double` | `TestUtils.pairedTTest(double[] sample1, double[] sample2)`
`double` | `TTest.pairedTTest(double[] sample1, double[] sample2)` Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
`static boolean` | `TestUtils.pairedTTest(double[] sample1, double[] sample2, double alpha)`
`boolean` | `TTest.pairedTTest(double[] sample1, double[] sample2, double alpha)` Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
`static double` | `TestUtils.t(double[] sample1, double[] sample2)`
`double` | `TTest.t(double[] sample1, double[] sample2)` Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
`static double` | `TestUtils.t(double mu, double[] observed)`
`double` | `TTest.t(double mu, double[] observed)` Computes a t statistic given observed values and a comparison constant.
`static double` | `TestUtils.t(double mu, StatisticalSummary sampleStats)`
`double` | `TTest.t(double mu, StatisticalSummary sampleStats)` Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
`static double` | `TestUtils.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double` | `TTest.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)` Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
`static double` | `TestUtils.tTest(double[] sample1, double[] sample2)`
`double` | `TTest.tTest(double[] sample1, double[] sample2)` Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
`static boolean` | `TestUtils.tTest(double[] sample1, double[] sample2, double alpha)`
`boolean` | `TTest.tTest(double[] sample1, double[] sample2, double alpha)` Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
`static double` | `TestUtils.tTest(double mu, double[] sample)`
`double` | `TTest.tTest(double mu, double[] sample)` Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant `mu`.
`static boolean` | `TestUtils.tTest(double mu, double[] sample, double alpha)`
`boolean` | `TTest.tTest(double mu, double[] sample, double alpha)` Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
`static double` | `TestUtils.tTest(double mu, StatisticalSummary sampleStats)`
`double` | `TTest.tTest(double mu, StatisticalSummary sampleStats)` Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
`static boolean` | `TestUtils.tTest(double mu, StatisticalSummary sampleStats, double alpha)`
`boolean` | `TTest.tTest(double mu, StatisticalSummary sampleStats, double alpha)` Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
`static double` | `TestUtils.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double` | `TTest.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)` Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
`static boolean` | `TestUtils.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)`
`boolean` | `TTest.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)` Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.

Uses of NumberIsTooSmallException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw NumberIsTooSmallException
`protected void` | `ResizableDoubleArray.checkContractExpand(double contraction, double expansion)` Checks the expansion factor and the contraction criterion and raises an exception if the contraction criterion is smaller than the expansion criterion.

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