Uses of Class org.apache.commons.math3.exception.ZeroException (Apache Commons Math 3.6.1 API)

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

- Packages that use ZeroException
  Package | Description
  --- | ---
  org.apache.commons.math3.analysis.interpolation | Univariate real functions interpolation algorithms.
  org.apache.commons.math3.complex | Complex number type and implementations of complex transcendental functions.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.random | Random number and random data generators.
  org.apache.commons.math3.stat.inference | Classes providing hypothesis testing.

- - ### Uses of ZeroException in org.apache.commons.math3.analysis.interpolation

    Methods in org.apache.commons.math3.analysis.interpolation that throw ZeroException
    Modifier and Type | Method and Description
    --- | ---
    `void` | HermiteInterpolator.`addSamplePoint(double x, double[]... value)` Add a sample point.
    `void` | FieldHermiteInterpolator.`addSamplePoint(T x, T[]... value)` Add a sample point.

  - ### Uses of ZeroException in org.apache.commons.math3.complex

    Methods in org.apache.commons.math3.complex that throw ZeroException
    Modifier and Type | Method and Description
    --- | ---
    `void` | RootsOfUnity.`computeRoots(int n)` Computes the `n`-th roots of unity.

  - ### Uses of ZeroException in org.apache.commons.math3.linear

    Methods in org.apache.commons.math3.linear that throw ZeroException
    Modifier and Type | Method and 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.math3.linear that throw ZeroException
    Constructor and 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.math3.random

    Methods in org.apache.commons.math3.random that throw ZeroException
    Modifier and Type | Method and Description
    --- | ---
    `void` | ValueServer.`computeDistribution()` Computes the empirical distribution using values from the file in `valuesFileURL`, using the default number of bins.
    `void` | ValueServer.`computeDistribution(int binCount)` Computes the empirical distribution using values from the file in `valuesFileURL` and `binCount` bins.
    `void` | EmpiricalDistribution.`load(URL url)` Computes 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 ZeroException
    Modifier and Type | Method and Description
    --- | ---
    `static double` | TestUtils.`chiSquareDataSetsComparison(long[] observed1, long[] observed2)`
    `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` | TestUtils.`chiSquareTestDataSetsComparison(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`.
    `static boolean` | TestUtils.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
    `boolean` | ChiSquareTest.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)` Performs a Chi-Square two sample test comparing two binned data sets.
    `static double` | TestUtils.`gDataSetsComparison(long[] observed1, long[] observed2)`
    `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` | TestUtils.`gTestDataSetsComparison(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`.
    `static boolean` | TestUtils.`gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
    `boolean` | GTest.`gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)` Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
    `static double` | TestUtils.`rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)`

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