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

- Packages that use NoDataException
  Package | Description
  --- | ---
  org.apache.commons.math3.analysis.polynomials | Univariate real polynomials implementations, seen as differentiable univariate real functions.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction.

- - ### Uses of NoDataException in org.apache.commons.math3.analysis.polynomials

    Methods in org.apache.commons.math3.analysis.polynomials that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `protected static double[]` | PolynomialFunction.`differentiate(double[] coefficients)` Returns the coefficients of the derivative of the polynomial with the given coefficients.
    `protected static double` | PolynomialFunction.`evaluate(double[] coefficients, double argument)` Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.

    Constructors in org.apache.commons.math3.analysis.polynomials that throw NoDataException
    Constructor and Description
    `PolynomialFunction(double[] c)` Construct a polynomial with the given coefficients.

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

    Methods in org.apache.commons.math3.linear that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `void` | AbstractRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)` Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
    `void` | BlockRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)` Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.

    Constructors in org.apache.commons.math3.linear that throw NoDataException
    Constructor and Description
    `Array2DRowFieldMatrix(Field<T> field, T[][] d, boolean copyArray)` Create a new `FieldMatrix<T>` using the input array as the underlying data array.
    `Array2DRowRealMatrix(double[][] d)` Create a new `RealMatrix` using the input array as the underlying data array.

  - ### Uses of NoDataException in org.apache.commons.math3.stat.inference

    Methods in org.apache.commons.math3.stat.inference that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `double` | MannWhitneyUTest.`mannWhitneyU(double[] x, double[] y)` Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length.
    `double` | MannWhitneyUTest.`mannWhitneyUTest(double[] x, double[] y)` Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U statistic comparing mean for two independent samples.
    `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.`pairedT(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 double` | TestUtils.`pairedTTest(double[] sample1, double[] sample2)`
    `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 boolean` | TestUtils.`pairedTTest(double[] sample1, double[] sample2, double alpha)`
    `double` | WilcoxonSignedRankTest.`wilcoxonSignedRank(double[] x, double[] y)` Computes the Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
    `double` | WilcoxonSignedRankTest.`wilcoxonSignedRankTest(double[] x, double[] y, boolean exactPValue)` Returns the observed significance level, or p-value, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.

Copyright © 2003-2012 The Apache Software Foundation. All Rights Reserved.