Uses of Class
org.apache.commons.math3.exception.MathIllegalArgumentException

Packages that use MathIllegalArgumentException
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.complex Complex number type and implementations of complex transcendental functions. 
org.apache.commons.math3.exception Specialized exceptions for algorithms errors. 
org.apache.commons.math3.fraction Fraction number type and fraction number formatting. 
org.apache.commons.math3.genetics This package provides Genetic Algorithms components and implementations. 
org.apache.commons.math3.geometry.euclidean.threed This package provides basic 3D geometry components. 
org.apache.commons.math3.geometry.euclidean.twod This package provides basic 2D geometry components. 
org.apache.commons.math3.linear Linear algebra support. 
org.apache.commons.math3.ml.clustering Clustering algorithms. 
org.apache.commons.math3.ode This package provides classes to solve Ordinary Differential Equations problems. 
org.apache.commons.math3.random Random number and random data generators. 
org.apache.commons.math3.stat Data storage, manipulation and summary routines. 
org.apache.commons.math3.stat.clustering All classes and sub-packages of this package are deprecated. 
org.apache.commons.math3.stat.correlation Correlations/Covariance computations. 
org.apache.commons.math3.stat.descriptive Generic univariate summary statistic objects. 
org.apache.commons.math3.stat.descriptive.moment Summary statistics based on moments. 
org.apache.commons.math3.stat.descriptive.rank Summary statistics based on ranks. 
org.apache.commons.math3.stat.descriptive.summary Other summary statistics. 
org.apache.commons.math3.stat.inference Classes providing hypothesis testing and confidence interval construction. 
org.apache.commons.math3.stat.regression Statistical routines involving multivariate data. 
org.apache.commons.math3.transform Implementations of transform methods, including Fast Fourier transforms. 
org.apache.commons.math3.util Convenience routines and common data structures used throughout the commons-math library. 
 

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

Methods in org.apache.commons.math3.analysis.differentiation that throw MathIllegalArgumentException
 DerivativeStructure[] UnivariateDifferentiableVectorFunction.value(DerivativeStructure x)
          Compute the value for the function.
 DerivativeStructure[][] UnivariateDifferentiableMatrixFunction.value(DerivativeStructure x)
          Compute the value for the function.
 DerivativeStructure[] MultivariateDifferentiableVectorFunction.value(DerivativeStructure[] point)
          Compute the value for the function at the given point.
 DerivativeStructure MultivariateDifferentiableFunction.value(DerivativeStructure[] point)
          Compute the value for the function at the given point.
 

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

Methods in org.apache.commons.math3.analysis.integration that throw MathIllegalArgumentException
protected  double LegendreGaussIntegrator.doIntegrate()
          Deprecated. Method for implementing actual integration algorithms in derived classes.
protected  double IterativeLegendreGaussIntegrator.doIntegrate()
          Method for implementing actual integration algorithms in derived classes.
protected  double TrapezoidIntegrator.doIntegrate()
          Method for implementing actual integration algorithms in derived classes.
 double UnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double min, double max)
          Integrate the function in the given interval.
 double BaseAbstractUnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double lower, double upper)
          Integrate the function in the given interval.
protected  void BaseAbstractUnivariateIntegrator.setup(int maxEval, UnivariateFunction f, double lower, double upper)
          Prepare for computation.
 

Constructors in org.apache.commons.math3.analysis.integration that throw MathIllegalArgumentException
LegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy)
          Deprecated. Build a Legendre-Gauss integrator with given accuracies.
LegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)
          Deprecated. Build a Legendre-Gauss integrator with given accuracies and iterations counts.
LegendreGaussIntegrator(int n, int minimalIterationCount, int maximalIterationCount)
          Deprecated. Build a Legendre-Gauss integrator with given iteration counts.
 

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

Methods in org.apache.commons.math3.analysis.interpolation that throw MathIllegalArgumentException
 MultivariateFunction MultivariateInterpolator.interpolate(double[][] xval, double[] yval)
          Computes an interpolating function for the data set.
 UnivariateFunction UnivariateInterpolator.interpolate(double[] xval, double[] yval)
          Compute an interpolating function for the dataset.
 

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

Methods in org.apache.commons.math3.analysis.solvers that throw MathIllegalArgumentException
 double BaseUnivariateSolver.solve(int maxEval, FUNC f, double min, double max)
          Solve for a zero root in the given interval.
 double BaseUnivariateSolver.solve(int maxEval, FUNC f, double min, double max, double startValue)
          Solve for a zero in the given interval, start at startValue.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.complex
 

Methods in org.apache.commons.math3.complex that throw MathIllegalArgumentException
 StringBuffer ComplexFormat.format(Object obj, StringBuffer toAppendTo, FieldPosition pos)
          Formats a object to produce a string.
 double RootsOfUnity.getReal(int k)
          Get the real part of the k-th n-th root of unity.
static Complex ComplexUtils.polar2Complex(double r, double theta)
          Creates a complex number from the given polar representation.
 

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

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.exception
 class DimensionMismatchException
          Exception to be thrown when two dimensions differ.
 class MathIllegalNumberException
          Base class for exceptions raised by a wrong number.
 class MultiDimensionMismatchException
          Exception to be thrown when two sets of dimensions differ.
 class NoBracketingException
          Exception to be thrown when function values have the same sign at both ends of an interval.
 class NoDataException
          Exception to be thrown when the required data is missing.
 class NonMonotonicSequenceException
          Exception to be thrown when the a sequence of values is not monotonically increasing or decreasing.
 class NotANumberException
          Exception to be thrown when a number is not a number.
 class NotFiniteNumberException
          Exception to be thrown when a number is not finite.
 class NotPositiveException
          Exception to be thrown when the argument is negative.
 class NotStrictlyPositiveException
          Exception to be thrown when the argument is negative.
 class NullArgumentException
          All conditions checks that fail due to a null argument must throw this exception.
 class NumberIsTooLargeException
          Exception to be thrown when a number is too large.
 class NumberIsTooSmallException
          Exception to be thrown when a number is too small.
 class OutOfRangeException
          Exception to be thrown when some argument is out of range.
 class ZeroException
          Exception to be thrown when zero is provided where it is not allowed.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.fraction
 

Methods in org.apache.commons.math3.fraction that throw MathIllegalArgumentException
 StringBuffer FractionFormat.format(Object obj, StringBuffer toAppendTo, FieldPosition pos)
          Formats an object and appends the result to a StringBuffer.
 

Constructors in org.apache.commons.math3.fraction that throw MathIllegalArgumentException
BigFraction(double value)
          Create a fraction given the double value.
 

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

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.genetics
 class InvalidRepresentationException
          Exception indicating that the representation of a chromosome is not valid.
 

Methods in org.apache.commons.math3.genetics that throw MathIllegalArgumentException
 ChromosomePair CrossoverPolicy.crossover(Chromosome first, Chromosome second)
          Perform a crossover operation on the given chromosomes.
 ChromosomePair CycleCrossover.crossover(Chromosome first, Chromosome second)
          Perform a crossover operation on the given chromosomes.
 ChromosomePair NPointCrossover.crossover(Chromosome first, Chromosome second)
          Performs a N-point crossover.
 ChromosomePair UniformCrossover.crossover(Chromosome first, Chromosome second)
          Perform a crossover operation on the given chromosomes.
 ChromosomePair OrderedCrossover.crossover(Chromosome first, Chromosome second)
          Perform a crossover operation on the given chromosomes.
 ChromosomePair OnePointCrossover.crossover(Chromosome first, Chromosome second)
          Performs one point crossover.
static
<S> List<Double>
RandomKey.inducedPermutation(List<S> originalData, List<S> permutedData)
          Generates a representation of a permutation corresponding to a permutation which yields permutedData when applied to originalData.
 Chromosome BinaryMutation.mutate(Chromosome original)
          Mutate the given chromosome.
 Chromosome RandomKeyMutation.mutate(Chromosome original)
          Mutate the given chromosome.
 Chromosome MutationPolicy.mutate(Chromosome original)
          Mutate the given chromosome.
 ChromosomePair SelectionPolicy.select(Population population)
          Select two chromosomes from the population.
 ChromosomePair TournamentSelection.select(Population population)
          Select two chromosomes from the population.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.geometry.euclidean.threed
 

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.geometry.euclidean.threed
 class NotARotationMatrixException
          This class represents exceptions thrown while building rotations from matrices.
 

Methods in org.apache.commons.math3.geometry.euclidean.threed that throw MathIllegalArgumentException
 void Line.reset(Vector3D p1, Vector3D p2)
          Reset the instance as if built from two points.
 

Constructors in org.apache.commons.math3.geometry.euclidean.threed that throw MathIllegalArgumentException
FieldRotation(FieldVector3D<T> axis, T angle)
          Build a rotation from an axis and an angle.
Line(Vector3D p1, Vector3D p2)
          Build a line from two points.
Rotation(Vector3D axis, double angle)
          Build a rotation from an axis and an angle.
SubLine(Segment segment)
          Create a sub-line from a segment.
SubLine(Vector3D start, Vector3D end)
          Create a sub-line from two endpoints.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.geometry.euclidean.twod
 

Methods in org.apache.commons.math3.geometry.euclidean.twod that throw MathIllegalArgumentException
static Transform<Euclidean2D,Euclidean1D> Line.getTransform(AffineTransform transform)
          Get a Transform embedding an affine transform.
 

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

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.linear
 class IllConditionedOperatorException
          An exception to be thrown when the condition number of a RealLinearOperator is too high.
 class MatrixDimensionMismatchException
          Exception to be thrown when either the number of rows or the number of columns of a matrix do not match the expected values.
 class NonPositiveDefiniteMatrixException
          Exception to be thrown when a positive definite matrix is expected.
 class NonPositiveDefiniteOperatorException
          Exception to be thrown when a symmetric, definite positive RealLinearOperator is expected.
 class NonSelfAdjointOperatorException
          Exception to be thrown when a self-adjoint RealLinearOperator is expected.
 class NonSquareMatrixException
          Exception to be thrown when a square matrix is expected.
 class NonSquareOperatorException
          Exception to be thrown when a square linear operator is expected.
 class NonSymmetricMatrixException
          Exception to be thrown when a symmetric matrix is expected.
 class SingularMatrixException
          Exception to be thrown when a non-singular matrix is expected.
 class SingularOperatorException
          Exception to be thrown when trying to invert a singular operator.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.ml.clustering
 

Methods in org.apache.commons.math3.ml.clustering that throw MathIllegalArgumentException
 List<CentroidCluster<T>> KMeansPlusPlusClusterer.cluster(Collection<T> points)
          Runs the K-means++ clustering algorithm.
abstract  List<? extends Cluster<T>> Clusterer.cluster(Collection<T> points)
          Perform a cluster analysis on the given set of Clusterable instances.
 List<CentroidCluster<T>> MultiKMeansPlusPlusClusterer.cluster(Collection<T> points)
          Runs the K-means++ clustering algorithm.
 

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

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.ode
static class JacobianMatrices.MismatchedEquations
          Special exception for equations mismatch.
 class UnknownParameterException
          Exception to be thrown when a parameter is unknown.
 

Methods in org.apache.commons.math3.ode that throw MathIllegalArgumentException
 void ContinuousOutputModel.append(ContinuousOutputModel model)
          Append another model at the end of the instance.
 void SecondOrderIntegrator.integrate(SecondOrderDifferentialEquations equations, double t0, double[] y0, double[] yDot0, double t, double[] y, double[] yDot)
          Integrate the differential equations up to the given time
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.random
 

Methods in org.apache.commons.math3.random that throw MathIllegalArgumentException
 void ValueServer.fill(double[] values)
          Fills the input array with values generated using getNext() repeatedly.
 double[] ValueServer.fill(int length)
          Returns an array of length length with values generated using getNext() repeatedly.
 double ValueServer.getNext()
          Returns the next generated value, generated according to the mode value (see MODE constants).
 int RandomDataImpl.nextInversionDeviate(IntegerDistribution distribution)
          Deprecated. use the distribution's sample() method
 double RandomDataImpl.nextInversionDeviate(RealDistribution distribution)
          Deprecated. use the distribution's sample() method
 

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

Methods in org.apache.commons.math3.stat that throw MathIllegalArgumentException
 void Frequency.addValue(char v)
          Adds 1 to the frequency count for v.
 void Frequency.addValue(Comparable<?> v)
          Adds 1 to the frequency count for v.
 void Frequency.addValue(int v)
          Adds 1 to the frequency count for v.
 void Frequency.addValue(long v)
          Adds 1 to the frequency count for v.
static double StatUtils.geometricMean(double[] values)
          Returns the geometric mean of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.geometricMean(double[] values, int begin, int length)
          Returns the geometric mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.max(double[] values)
          Returns the maximum of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.max(double[] values, int begin, int length)
          Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.mean(double[] values)
          Returns the arithmetic mean of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.mean(double[] values, int begin, int length)
          Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.min(double[] values)
          Returns the minimum of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.min(double[] values, int begin, int length)
          Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.percentile(double[] values, double p)
          Returns an estimate of the pth percentile of the values in the values array.
static double StatUtils.percentile(double[] values, int begin, int length, double p)
          Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
static double StatUtils.populationVariance(double[] values)
          Returns the population variance of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.populationVariance(double[] values, double mean)
          Returns the population variance of the entries in the input array, using the precomputed mean value.
static double StatUtils.populationVariance(double[] values, double mean, int begin, int length)
          Returns the population variance of the entries in the specified portion of the input array, using the precomputed mean value.
static double StatUtils.populationVariance(double[] values, int begin, int length)
          Returns the population variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.product(double[] values)
          Returns the product of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.product(double[] values, int begin, int length)
          Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.sum(double[] values)
          Returns the sum of the values in the input array, or Double.NaN if the array is empty.
static double StatUtils.sum(double[] values, int begin, int length)
          Returns the sum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.sumLog(double[] values)
          Returns the sum of the natural logs of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.sumLog(double[] values, int begin, int length)
          Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.sumSq(double[] values)
          Returns the sum of the squares of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.sumSq(double[] values, int begin, int length)
          Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double StatUtils.variance(double[] values)
          Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
static double StatUtils.variance(double[] values, double mean)
          Returns the variance of the entries in the input array, using the precomputed mean value.
static double StatUtils.variance(double[] values, double mean, int begin, int length)
          Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
static double StatUtils.variance(double[] values, int begin, int length)
          Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.clustering
 

Methods in org.apache.commons.math3.stat.clustering that throw MathIllegalArgumentException
 List<Cluster<T>> KMeansPlusPlusClusterer.cluster(Collection<T> points, int k, int maxIterations)
          Deprecated. Runs the K-means++ clustering algorithm.
 List<Cluster<T>> KMeansPlusPlusClusterer.cluster(Collection<T> points, int k, int numTrials, int maxIterationsPerTrial)
          Deprecated. Runs the K-means++ clustering algorithm.
 

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

Methods in org.apache.commons.math3.stat.correlation that throw MathIllegalArgumentException
protected  RealMatrix Covariance.computeCovarianceMatrix(double[][] data)
          Create a covariance matrix from a rectangular array whose columns represent covariates.
protected  RealMatrix Covariance.computeCovarianceMatrix(double[][] data, boolean biasCorrected)
          Compute a covariance matrix from a rectangular array whose columns represent covariates.
protected  RealMatrix Covariance.computeCovarianceMatrix(RealMatrix matrix)
          Create a covariance matrix from a matrix whose columns represent covariates.
protected  RealMatrix Covariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected)
          Compute a covariance matrix from a matrix whose columns represent covariates.
 double Covariance.covariance(double[] xArray, double[] yArray)
          Computes the covariance between the two arrays, using the bias-corrected formula.
 double Covariance.covariance(double[] xArray, double[] yArray, boolean biasCorrected)
          Computes the covariance between the two arrays.
 

Constructors in org.apache.commons.math3.stat.correlation that throw MathIllegalArgumentException
Covariance(double[][] data)
          Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(double[][] data, boolean biasCorrected)
          Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(RealMatrix matrix)
          Create a covariance matrix from a matrix whose columns represent covariates.
Covariance(RealMatrix matrix, boolean biasCorrected)
          Create a covariance matrix from a matrix whose columns represent covariates.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.descriptive
 

Methods in org.apache.commons.math3.stat.descriptive that throw MathIllegalArgumentException
 double AbstractUnivariateStatistic.evaluate()
          Returns the result of evaluating the statistic over the stored data.
 double AbstractUnivariateStatistic.evaluate(double[] values)
          Returns the result of evaluating the statistic over the input array.
 double AbstractStorelessUnivariateStatistic.evaluate(double[] values)
          This default implementation calls AbstractStorelessUnivariateStatistic.clear(), then invokes AbstractStorelessUnivariateStatistic.increment(double) in a loop over the the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
 double UnivariateStatistic.evaluate(double[] values)
          Returns the result of evaluating the statistic over the input array.
 double WeightedEvaluation.evaluate(double[] values, double[] weights)
          Returns the result of evaluating the statistic over the input array, using the supplied weights.
 double WeightedEvaluation.evaluate(double[] values, double[] weights, int begin, int length)
          Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.
abstract  double AbstractUnivariateStatistic.evaluate(double[] values, int begin, int length)
          Returns the result of evaluating the statistic over the specified entries in the input array.
 double AbstractStorelessUnivariateStatistic.evaluate(double[] values, int begin, int length)
          This default implementation calls AbstractStorelessUnivariateStatistic.clear(), then invokes AbstractStorelessUnivariateStatistic.increment(double) in a loop over the specified portion of the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
 double UnivariateStatistic.evaluate(double[] values, int begin, int length)
          Returns the result of evaluating the statistic over the specified entries in the input array.
 double DescriptiveStatistics.getPercentile(double p)
          Returns an estimate for the pth percentile of the stored values.
 void StorelessUnivariateStatistic.incrementAll(double[] values)
          Updates the internal state of the statistic to reflect addition of all values in the values array.
 void AbstractStorelessUnivariateStatistic.incrementAll(double[] values)
          This default implementation just calls AbstractStorelessUnivariateStatistic.increment(double) in a loop over the input array.
 void StorelessUnivariateStatistic.incrementAll(double[] values, int start, int length)
          Updates the internal state of the statistic to reflect addition of the values in the designated portion of the values array.
 void AbstractStorelessUnivariateStatistic.incrementAll(double[] values, int begin, int length)
          This default implementation just calls AbstractStorelessUnivariateStatistic.increment(double) in a loop over the specified portion of the input array.
 void AbstractUnivariateStatistic.setData(double[] values, int begin, int length)
          Set the data array.
 void DescriptiveStatistics.setPercentileImpl(UnivariateStatistic percentileImpl)
          Sets the implementation to be used by DescriptiveStatistics.getPercentile(double).
 void DescriptiveStatistics.setWindowSize(int windowSize)
          WindowSize controls the number of values that contribute to the reported statistics.
 void SynchronizedDescriptiveStatistics.setWindowSize(int windowSize)
          WindowSize controls the number of values that contribute to the reported statistics.
protected  boolean AbstractUnivariateStatistic.test(double[] values, double[] weights, int begin, int length)
          This method is used by evaluate(double[], double[], int, int) methods to verify that the begin and length parameters designate a subarray of positive length and the weights are all non-negative, non-NaN, finite, and not all zero.
protected  boolean AbstractUnivariateStatistic.test(double[] values, double[] weights, int begin, int length, boolean allowEmpty)
          This method is used by evaluate(double[], double[], int, int) methods to verify that the begin and length parameters designate a subarray of positive length and the weights are all non-negative, non-NaN, finite, and not all zero.
protected  boolean AbstractUnivariateStatistic.test(double[] values, int begin, int length)
          This method is used by evaluate(double[], int, int) methods to verify that the input parameters designate a subarray of positive length.
protected  boolean AbstractUnivariateStatistic.test(double[] values, int begin, int length, boolean allowEmpty)
          This method is used by evaluate(double[], int, int) methods to verify that the input parameters designate a subarray of positive length.
 

Constructors in org.apache.commons.math3.stat.descriptive that throw MathIllegalArgumentException
DescriptiveStatistics(int window)
          Construct a DescriptiveStatistics instance with the specified window
SynchronizedDescriptiveStatistics(int window)
          Construct an instance with finite window
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.descriptive.moment
 

Methods in org.apache.commons.math3.stat.descriptive.moment that throw MathIllegalArgumentException
 double Variance.evaluate(double[] values)
          Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
 double StandardDeviation.evaluate(double[] values)
          Returns the Standard Deviation of the entries in the input array, or Double.NaN if the array is empty.
 double Variance.evaluate(double[] values, double mean)
          Returns the variance of the entries in the input array, using the precomputed mean value.
 double StandardDeviation.evaluate(double[] values, double mean)
          Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
 double SemiVariance.evaluate(double[] values, double cutoff)
          Returns the SemiVariance of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
 double Variance.evaluate(double[] values, double[] weights)
           Returns the weighted variance of the entries in the the input array.
 double Mean.evaluate(double[] values, double[] weights)
          Returns the weighted arithmetic mean of the entries in the input array.
 double Variance.evaluate(double[] values, double[] weights, double mean)
          Returns the weighted variance of the values in the input array, using the precomputed weighted mean value.
 double Variance.evaluate(double[] values, double[] weights, double mean, int begin, int length)
          Returns the weighted variance of the entries in the specified portion of the input array, using the precomputed weighted mean value.
 double Variance.evaluate(double[] values, double[] weights, int begin, int length)
          Returns the weighted variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Mean.evaluate(double[] values, double[] weights, int begin, int length)
          Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Variance.evaluate(double[] values, double mean, int begin, int length)
          Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
 double StandardDeviation.evaluate(double[] values, double mean, int begin, int length)
          Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
 double SemiVariance.evaluate(double[] values, double cutoff, SemiVariance.Direction direction)
          Returns the SemiVariance of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.
 double SemiVariance.evaluate(double[] values, double cutoff, SemiVariance.Direction direction, boolean corrected, int start, int length)
          Returns the SemiVariance of the designated values against the cutoff in the given direction with the provided bias correction.
 double Variance.evaluate(double[] values, int begin, int length)
          Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double GeometricMean.evaluate(double[] values, int begin, int length)
          Returns the geometric mean of the entries in the specified portion of the input array.
 double StandardDeviation.evaluate(double[] values, int begin, int length)
          Returns the Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Skewness.evaluate(double[] values, int begin, int length)
          Returns the Skewness of the entries in the specifed portion of the input array.
 double Mean.evaluate(double[] values, int begin, int length)
          Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double SemiVariance.evaluate(double[] values, int start, int length)
          Returns the SemiVariance of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
 double Kurtosis.evaluate(double[] values, int begin, int length)
          Returns the kurtosis of the entries in the specified portion of the input array.
 double SemiVariance.evaluate(double[] values, SemiVariance.Direction direction)
          This method calculates SemiVariance for the entire array against the mean, using the current value of the biasCorrection instance property.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.descriptive.rank
 

Methods in org.apache.commons.math3.stat.descriptive.rank that throw MathIllegalArgumentException
 double Percentile.evaluate(double p)
          Returns the result of evaluating the statistic over the stored data.
 double Percentile.evaluate(double[] values, double p)
          Returns an estimate of the pth percentile of the values in the values array.
 double Max.evaluate(double[] values, int begin, int length)
          Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Min.evaluate(double[] values, int begin, int length)
          Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Percentile.evaluate(double[] values, int start, int length)
          Returns an estimate of the quantileth percentile of the designated values in the values array.
 double Percentile.evaluate(double[] values, int begin, int length, double p)
          Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
 void Percentile.setData(double[] values, int begin, int length)
          Set the data array.
 void Percentile.setQuantile(double p)
          Sets the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
 

Constructors in org.apache.commons.math3.stat.descriptive.rank that throw MathIllegalArgumentException
Percentile(double p)
          Constructs a Percentile with the specific quantile value.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.descriptive.summary
 

Methods in org.apache.commons.math3.stat.descriptive.summary that throw MathIllegalArgumentException
 double Product.evaluate(double[] values, double[] weights)
          Returns the weighted product of the entries in the input array.
 double Sum.evaluate(double[] values, double[] weights)
          The weighted sum of the entries in the the input array.
 double Product.evaluate(double[] values, double[] weights, int begin, int length)
          Returns the weighted product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Sum.evaluate(double[] values, double[] weights, int begin, int length)
          The weighted sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
 double Product.evaluate(double[] values, int begin, int length)
          Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double SumOfLogs.evaluate(double[] values, int begin, int length)
          Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 double Sum.evaluate(double[] values, int begin, int length)
          The sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
 double SumOfSquares.evaluate(double[] values, int begin, int length)
          Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
 

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

Methods in org.apache.commons.math3.stat.inference that throw MathIllegalArgumentException
protected  double TTest.tTest(double m, double mu, double v, double n)
          Computes p-value for 2-sided, 1-sample t-test.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.stat.regression
 

Subclasses of MathIllegalArgumentException in org.apache.commons.math3.stat.regression
 class ModelSpecificationException
          Exception thrown when a regression model is not correctly specified.
 

Methods in org.apache.commons.math3.stat.regression that throw MathIllegalArgumentException
 double OLSMultipleLinearRegression.calculateAdjustedRSquared()
          Returns the adjusted R-squared statistic, defined by the formula R2adj = 1 - [SSR (n - 1)] / [SSTO (n - p)] where SSR is the sum of squared residuals, SSTO is the total sum of squares, n is the number of observations and p is the number of parameters estimated (including the intercept).
 double OLSMultipleLinearRegression.calculateRSquared()
          Returns the R-Squared statistic, defined by the formula R2 = 1 - SSR / SSTO where SSR is the sum of squared residuals and SSTO is the total sum of squares
 double OLSMultipleLinearRegression.calculateTotalSumOfSquares()
          Returns the sum of squared deviations of Y from its mean.
 void OLSMultipleLinearRegression.newSampleData(double[] y, double[][] x)
          Loads model x and y sample data, overriding any previous sample.
 RegressionResults UpdatingMultipleLinearRegression.regress(int[] variablesToInclude)
          Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object
 RegressionResults SimpleRegression.regress(int[] variablesToInclude)
          Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object
protected  void AbstractMultipleLinearRegression.validateSampleData(double[][] x, double[] y)
          Validates sample data.
 

Uses of MathIllegalArgumentException in org.apache.commons.math3.transform
 

Methods in org.apache.commons.math3.transform that throw MathIllegalArgumentException
static int TransformUtils.exactLog2(int n)
          Returns the base-2 logarithm of the specified int.
protected  double[] FastCosineTransformer.fct(double[] f)
          Perform the FCT algorithm (including inverse).
protected  double[] FastHadamardTransformer.fht(double[] x)
          The FHT (Fast Hadamard Transformation) which uses only subtraction and addition.
protected  int[] FastHadamardTransformer.fht(int[] x)
          Returns the forward transform of the specified integer data set.
protected  double[] FastSineTransformer.fst(double[] f)
          Perform the FST algorithm (including inverse).
 double[] FastCosineTransformer.transform(double[] f, TransformType type)
          Returns the (forward, inverse) transform of the specified real data set.
 double[] RealTransformer.transform(double[] f, TransformType type)
          Returns the (forward, inverse) transform of the specified real data set.
 double[] FastCosineTransformer.transform(UnivariateFunction f, double min, double max, int n, TransformType type)
          Returns the (forward, inverse) transform of the specified real function, sampled on the specified interval.
 double[] RealTransformer.transform(UnivariateFunction f, double min, double max, int n, TransformType type)
          Returns the (forward, inverse) transform of the specified real function, sampled on the specified interval.
 

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

Methods in org.apache.commons.math3.util that throw MathIllegalArgumentException
protected  void ResizableDoubleArray.checkContractExpand(float contraction, float expansion)
          Deprecated. As of 3.1. Please use ResizableDoubleArray.checkContractExpand(double,double) instead.
 void ResizableDoubleArray.discardFrontElements(int i)
          Discards the i initial elements of the array.
 void ResizableDoubleArray.discardMostRecentElements(int i)
          Discards the i last elements of the array.
static double[] MathArrays.normalizeArray(double[] values, double normalizedSum)
          Normalizes an array to make it sum to a specified value.
static float Precision.round(float x, int scale, int roundingMethod)
          Rounds the given value to the specified number of decimal places.
 void ResizableDoubleArray.setContractionCriteria(float contractionCriteria)
          Deprecated. As of 3.1 (to be removed in 4.0 as field will become "final").
 void ResizableDoubleArray.setExpansionFactor(float expansionFactor)
          Deprecated. As of 3.1 (to be removed in 4.0 as field will become "final").
 void ResizableDoubleArray.setExpansionMode(int expansionMode)
          Deprecated. As of 3.1. Please use ResizableDoubleArray.setExpansionMode(ExpansionMode) instead.
protected  void ResizableDoubleArray.setInitialCapacity(int initialCapacity)
          Deprecated. As of 3.1, this is a no-op.
 void ResizableDoubleArray.setNumElements(int i)
          This function allows you to control the number of elements contained in this array, and can be used to "throw out" the last n values in an array.
 double NumberTransformer.transform(Object o)
          Implementing this interface provides a facility to transform from Object to Double.
 double TransformerMap.transform(Object o)
          Attempts to transform the Object against the map of NumberTransformers.
 double DefaultTransformer.transform(Object o)
           
 

Constructors in org.apache.commons.math3.util that throw MathIllegalArgumentException
ResizableDoubleArray(int initialCapacity)
          Creates an instance with the specified initial capacity.
ResizableDoubleArray(int initialCapacity, double expansionFactor)
          Creates an instance with the specified initial capacity and expansion factor.
ResizableDoubleArray(int initialCapacity, double expansionFactor, double contractionCriterion)
          Creates an instance with the specified initial capacity, expansion factor, and contraction criteria.
ResizableDoubleArray(int initialCapacity, double expansionFactor, double contractionCriterion, ResizableDoubleArray.ExpansionMode expansionMode, double... data)
          Creates an instance with the specified properties.
ResizableDoubleArray(int initialCapacity, float expansionFactor)
          Deprecated. As of 3.1. Please use ResizableDoubleArray.ResizableDoubleArray(int,double) instead.
ResizableDoubleArray(int initialCapacity, float expansionFactor, float contractionCriteria)
          Deprecated. As of 3.1. Please use ResizableDoubleArray.ResizableDoubleArray(int,double,double) instead.
ResizableDoubleArray(int initialCapacity, float expansionFactor, float contractionCriteria, int expansionMode)
          Deprecated. As of 3.1. Please use ResizableDoubleArray.ResizableDoubleArray(int,double,double,ExpansionMode,double[]) instead.
 



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