Uses of Class
org.apache.commons.math3.exception.ZeroException
Packages that use ZeroException
Package
Description
Univariate real functions interpolation algorithms.
Complex number type and implementations of complex transcendental
functions.
Linear algebra support.
Random number and random data generators.
Classes providing hypothesis testing.
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Uses of ZeroException in org.apache.commons.math3.analysis.interpolation
Methods in org.apache.commons.math3.analysis.interpolation that throw ZeroExceptionModifier and TypeMethodDescriptionvoidFieldHermiteInterpolator.addSamplePoint(T x, T[]... value) Add a sample point.voidHermiteInterpolator.addSamplePoint(double x, double[]... value) Add a sample point. -
Uses of ZeroException in org.apache.commons.math3.complex
Methods in org.apache.commons.math3.complex that throw ZeroExceptionModifier and TypeMethodDescriptionvoidRootsOfUnity.computeRoots(int n) Computes then-th roots of unity. -
Uses of ZeroException in org.apache.commons.math3.linear
Methods in org.apache.commons.math3.linear that throw ZeroExceptionModifier and TypeMethodDescriptionstatic <T extends FieldElement<T>>
FieldVector<T> MatrixUtils.createFieldVector(T[] data) Creates aFieldVectorusing the data from the input array.Constructors in org.apache.commons.math3.linear that throw ZeroExceptionModifierConstructorDescriptionArrayFieldVector(Field<T> field, T[] v1, T[] v2) Construct a vector by appending one vector to another vector.ArrayFieldVector(T[] d) Construct a vector from an array, copying the input array.ArrayFieldVector(T[] d, boolean copyArray) Create a new ArrayFieldVector using the input array as the underlying data array.ArrayFieldVector(T[] v1, T[] v2) Construct a vector by appending one vector to another vector. -
Uses of ZeroException in org.apache.commons.math3.random
Methods in org.apache.commons.math3.random that throw ZeroExceptionModifier and TypeMethodDescriptionvoidValueServer.computeDistribution()Computes the empirical distribution using values from the file invaluesFileURL, using the default number of bins.voidValueServer.computeDistribution(int binCount) Computes the empirical distribution using values from the file invaluesFileURLandbinCountbins.voidComputes the empirical distribution using data read from a URL. -
Uses of ZeroException in org.apache.commons.math3.stat.inference
Methods in org.apache.commons.math3.stat.inference that throw ZeroExceptionModifier and TypeMethodDescriptiondoubleChiSquareTest.chiSquareDataSetsComparison(long[] observed1, long[] observed2) Computes a Chi-Square two sample test statistic comparing bin frequency counts inobserved1andobserved2.static doubleTestUtils.chiSquareDataSetsComparison(long[] observed1, long[] observed2) doubleChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts inobserved1andobserved2.booleanChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha) Performs a Chi-Square two sample test comparing two binned data sets.static doubleTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2) static booleanTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha) doubleGTest.gDataSetsComparison(long[] observed1, long[] observed2) Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts inobserved1andobserved2.static doubleTestUtils.gDataSetsComparison(long[] observed1, long[] observed2) doubleGTest.gTestDataSetsComparison(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts inobserved1andobserved2.booleanGTest.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha) Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.static doubleTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2) static booleanTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha) static doubleTestUtils.rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)