Uses of Class org.apache.commons.math3.exception.NoDataException (Apache Commons Math 3.3 API)

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

- Packages that use NoDataException
  Package | Description
  --- | ---
  org.apache.commons.math3.analysis.function | The `function` package contains function objects that wrap the methods contained in `Math`, as well as common mathematical functions such as the gaussian and sinc functions.
  org.apache.commons.math3.analysis.interpolation | Univariate real functions interpolation algorithms.
  org.apache.commons.math3.analysis.polynomials | Univariate real polynomials implementations, seen as differentiable univariate real functions.
  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.filter | Implementations of common discrete-time linear filters.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.stat | Data storage, manipulation and summary routines.
  org.apache.commons.math3.stat.inference | Classes providing hypothesis testing.
  org.apache.commons.math3.stat.regression | Statistical routines involving multivariate data.
  org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library.

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

    Constructors in org.apache.commons.math3.analysis.function that throw NoDataException
    Constructor and Description
    `StepFunction(double[] x, double[] y)` Builds a step function from a list of arguments and the corresponding values.

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

    Methods in org.apache.commons.math3.analysis.interpolation that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `T[][]` | FieldHermiteInterpolator.`derivatives(T x, int order)` Interpolate value and first derivatives at a specified abscissa.
    `PolynomialFunction[]` | HermiteInterpolator.`getPolynomials()` Compute the interpolation polynomials.
    `MultivariateFunction` | MicrosphereInterpolator.`interpolate(double[][] xval, double[] yval)` Computes an interpolating function for the data set.
    `MultivariateFunction` | MultivariateInterpolator.`interpolate(double[][] xval, double[] yval)` Computes an interpolating function for the data set.
    `PolynomialSplineFunction` | LoessInterpolator.`interpolate(double[] xval, double[] yval)` Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a `SplineInterpolator` on the resulting fit.
    `BivariateFunction` | BivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Compute an interpolating function for the dataset.
    `BicubicSplineInterpolatingFunction` | SmoothingPolynomialBicubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Compute an interpolating function for the dataset.
    `BicubicSplineInterpolatingFunction` | BicubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Compute an interpolating function for the dataset.
    `TrivariateFunction` | TrivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)` Compute an interpolating function for the dataset.
    `TricubicSplineInterpolatingFunction` | TricubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)` Compute an interpolating function for the dataset.
    `double[]` | LoessInterpolator.`smooth(double[] xval, double[] yval)` Compute a loess fit on the data at the original abscissae.
    `double[]` | LoessInterpolator.`smooth(double[] xval, double[] yval, double[] weights)` Compute a weighted loess fit on the data at the original abscissae.
    `DerivativeStructure[]` | HermiteInterpolator.`value(DerivativeStructure x)` Interpolate value at a specified abscissa.
    `double[]` | HermiteInterpolator.`value(double x)` Interpolate value at a specified abscissa.
    `T[]` | FieldHermiteInterpolator.`value(T x)` Interpolate value at a specified abscissa.

    Constructors in org.apache.commons.math3.analysis.interpolation that throw NoDataException
    Constructor and Description
    `BicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY)`
    `MicrosphereInterpolatingFunction(double[][] xval, double[] yval, int brightnessExponent, int microsphereElements, UnitSphereRandomVectorGenerator rand)`
    `TricubicSplineInterpolatingFunction(double[] x, double[] y, double[] z, double[][][] f, double[][][] dFdX, double[][][] dFdY, double[][][] dFdZ, double[][][] d2FdXdY, double[][][] d2FdXdZ, double[][][] d2FdYdZ, double[][][] d3FdXdYdZ)`

  - ### 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.
    `static double` | PolynomialFunctionNewtonForm.`evaluate(double[] a, double[] c, double z)` Evaluate the Newton polynomial using nested multiplication.
    `DerivativeStructure` | PolynomialFunction.`value(DerivativeStructure t)` Simple mathematical function.
    `double` | PolynomialFunction.Parametric.`value(double x, double... parameters)` Compute the value of the function.
    `protected static void` | PolynomialFunctionNewtonForm.`verifyInputArray(double[] a, double[] c)` Verifies that the input arrays are valid.

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

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

    Methods in org.apache.commons.math3.analysis.solvers that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `Complex[]` | LaguerreSolver.`solveAllComplex(double[] coefficients, double initial)` Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
    `Complex` | LaguerreSolver.`solveComplex(double[] coefficients, double initial)` Find a complex root for the polynomial with the given coefficients, starting from the given initial value.

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

    Methods in org.apache.commons.math3.complex that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `static ComplexFormat` | ComplexFormat.`getInstance(String imaginaryCharacter, Locale locale)` Returns the default complex format for the given locale.

    Constructors in org.apache.commons.math3.complex that throw NoDataException
    Constructor and Description
    `ComplexFormat(String imaginaryCharacter)` Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
    `ComplexFormat(String imaginaryCharacter, NumberFormat format)` Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
    `ComplexFormat(String imaginaryCharacter, NumberFormat realFormat, NumberFormat imaginaryFormat)` Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.

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

    Constructors in org.apache.commons.math3.filter that throw NoDataException
    Constructor and Description
    `DefaultMeasurementModel(double[][] measMatrix, double[][] measNoise)` Create a new `MeasurementModel`, taking double arrays as input parameters for the respective measurement matrix and noise.
    `DefaultProcessModel(double[][] stateTransition, double[][] control, double[][] processNoise)` Create a new `ProcessModel`, taking double arrays as input parameters.
    `DefaultProcessModel(double[][] stateTransition, double[][] control, double[][] processNoise, double[] initialStateEstimate, double[][] initialErrorCovariance)` Create a new `ProcessModel`, taking double arrays as input parameters.

  - ### 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
    --- | ---
    `static void` | MatrixUtils.`checkSubMatrixIndex(AnyMatrix m, int[] selectedRows, int[] selectedColumns)` Check if submatrix ranges indices are valid.
    `protected void` | AbstractFieldMatrix.`checkSubMatrixIndex(int[] selectedRows, int[] selectedColumns)` Check if submatrix ranges indices are valid.
    `void` | AbstractRealMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)` Copy a submatrix.
    `void` | RealMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)` Copy a submatrix.
    `void` | FieldMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)` Copy a submatrix.
    `void` | AbstractFieldMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)` Copy a submatrix.
    `static <T extends FieldElement<T>> FieldMatrix<T>` | MatrixUtils.`createColumnFieldMatrix(T[] columnData)` Creates a column `FieldMatrix` using the data from the input array.
    `static RealMatrix` | MatrixUtils.`createColumnRealMatrix(double[] columnData)` Creates a column `RealMatrix` using the data from the input array.
    `static <T extends FieldElement<T>> FieldMatrix<T>` | MatrixUtils.`createFieldMatrix(T[][] data)` Returns a `FieldMatrix` whose entries are the the values in the the input array.
    `static <T extends FieldElement<T>> FieldVector<T>` | MatrixUtils.`createFieldVector(T[] data)` Creates a `FieldVector` using the data from the input array.
    `static RealMatrix` | MatrixUtils.`createRealMatrix(double[][] data)` Returns a `RealMatrix` whose entries are the the values in the the input array.
    `static RealVector` | MatrixUtils.`createRealVector(double[] data)` Creates a `RealVector` using the data from the input array.
    `static <T extends FieldElement<T>> FieldMatrix<T>` | MatrixUtils.`createRowFieldMatrix(T[] rowData)` Create a row `FieldMatrix` using the data from the input array.
    `static RealMatrix` | MatrixUtils.`createRowRealMatrix(double[] rowData)` Create a row `RealMatrix` using the data from the input array.
    `protected static <T extends FieldElement<T>> Field<T>` | AbstractFieldMatrix.`extractField(T[] d)` Get the elements type from an array.
    `protected static <T extends FieldElement<T>> Field<T>` | AbstractFieldMatrix.`extractField(T[][] d)` Get the elements type from an array.
    `FieldMatrix<T>` | FieldMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)` Get a submatrix.
    `FieldMatrix<T>` | AbstractFieldMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)` Get a submatrix.
    `RealMatrix` | AbstractRealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)` Gets a submatrix.
    `RealMatrix` | RealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)` Gets a submatrix.
    `void` | Array2DRowRealMatrix.`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.
    `void` | AbstractRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)` Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
    `void` | RealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)` Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
    `void` | BlockFieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)` Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
    `void` | FieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)` Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
    `void` | AbstractFieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)` Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
    `void` | Array2DRowFieldMatrix.`setSubMatrix(T[][] 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)` Create a new `FieldMatrix<T>` using the input array as the underlying data array.
    `Array2DRowFieldMatrix(Field<T> field, T[][] d, boolean copyArray)` Create a new `FieldMatrix<T>` using the input array as the underlying data array.
    `Array2DRowFieldMatrix(T[] v)` Create a new (column) `FieldMatrix<T>` using `v` as the data for the unique column of the created matrix.
    `Array2DRowFieldMatrix(T[][] d)` Create a new `FieldMatrix<T>` using the input array as the underlying data array.
    `Array2DRowFieldMatrix(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.
    `Array2DRowRealMatrix(double[][] d, boolean copyArray)` Create a new RealMatrix using the input array as the underlying data array.

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

    Methods in org.apache.commons.math3.stat that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `static double` | StatUtils.`meanDifference(double[] sample1, double[] sample2)` Returns the mean of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
    `static double` | StatUtils.`sumDifference(double[] sample1, double[] sample2)` Returns the sum of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]).

  - ### 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.

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

    Methods in org.apache.commons.math3.stat.regression that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `RegressionResults` | UpdatingMultipleLinearRegression.`regress()` Performs a regression on data present in buffers and outputs a RegressionResults object
    `RegressionResults` | SimpleRegression.`regress()` Performs a regression on data present in buffers and outputs a RegressionResults object.

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

    Methods in org.apache.commons.math3.util that throw NoDataException
    Modifier and Type | Method and Description
    --- | ---
    `static double[]` | MathArrays.`convolve(double[] x, double[] h)` Calculates the convolution between two sequences.

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