Uses of Class
org.apache.commons.math4.legacy.exception.ZeroException

Packages that use ZeroException

Package	Description
org.apache.commons.math4.legacy.analysis.interpolation	Univariate real functions interpolation algorithms.
org.apache.commons.math4.legacy.linear	Linear algebra support.
org.apache.commons.math4.legacy.stat.inference	Classes providing hypothesis testing.

Uses of ZeroException in org.apache.commons.math4.legacy.analysis.interpolation

Methods in org.apache.commons.math4.legacy.analysis.interpolation that throw ZeroException

Modifier and Type	Method	Description
void	FieldHermiteInterpolator.addSamplePoint(T x, T[]... value)	Add a sample point.
void	HermiteInterpolator.addSamplePoint(double x, double[]... value)	Add a sample point.

Uses of ZeroException in org.apache.commons.math4.legacy.linear

Methods in org.apache.commons.math4.legacy.linear that throw ZeroException

Modifier and Type	Method	Description
static <T extends FieldElement<T>> FieldVector<T>	MatrixUtils.createFieldVector(T[] data)	Creates a FieldVector using the data from the input array.

Constructors in org.apache.commons.math4.legacy.linear that throw ZeroException

Constructor	Description
ArrayFieldVector(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.math4.legacy.stat.inference

Methods in org.apache.commons.math4.legacy.stat.inference that throw ZeroException

Modifier and Type	Method	Description
double	ChiSquareTest.chiSquareDataSetsComparison(long[] observed1, long[] observed2)	Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2.
static double	InferenceTestUtils.chiSquareDataSetsComparison(long[] observed1, long[] observed2)
double	ChiSquareTest.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 in observed1 and observed2.
boolean	ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a Chi-Square two sample test comparing two binned data sets.
static double	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
double	GTest.gDataSetsComparison(long[] observed1, long[] observed2)	Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2.
static double	InferenceTestUtils.gDataSetsComparison(long[] observed1, long[] observed2)
double	GTest.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 in observed1 and observed2.
boolean	GTest.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
static double	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
static double	InferenceTestUtils.rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)