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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