Uses of Class
org.apache.commons.math4.exception.NoDataException

Packages that use NoDataException

Package	Description
org.apache.commons.math4.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.math4.analysis.interpolation	Univariate real functions interpolation algorithms.
org.apache.commons.math4.analysis.polynomials	Univariate real polynomials implementations, seen as differentiable univariate real functions.
org.apache.commons.math4.analysis.solvers	Root finding algorithms, for univariate real functions.
org.apache.commons.math4.linear	Linear algebra support.
org.apache.commons.math4.stat	Data storage, manipulation and summary routines.
org.apache.commons.math4.stat.inference	Classes providing hypothesis testing.
org.apache.commons.math4.stat.regression	Statistical routines involving multivariate data.
org.apache.commons.math4.util	Convenience routines and common data structures used throughout the commons-math library.

Uses of NoDataException in org.apache.commons.math4.analysis.function

Constructors in org.apache.commons.math4.analysis.function that throw NoDataException

Constructor	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.math4.analysis.interpolation

Methods in org.apache.commons.math4.analysis.interpolation that throw NoDataException

Modifier and Type	Method	Description
T[][]	FieldHermiteInterpolator.derivatives(T x, int order)	Interpolate value and first derivatives at a specified abscissa.
PolynomialFunction[]	HermiteInterpolator.getPolynomials()	Compute the interpolation polynomials.
BicubicInterpolatingFunction	BicubicInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
BivariateFunction	BivariateGridInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
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.
MultivariateFunction	MicrosphereProjectionInterpolator.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.
PiecewiseBicubicSplineInterpolatingFunction	PiecewiseBicubicSplineInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
TricubicInterpolatingFunction	TricubicInterpolator.interpolate(double[] xval, double[] yval, double[] zval, 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.
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.
T[]	FieldHermiteInterpolator.value(T x)	Interpolate value at a specified abscissa.
double[]	HermiteInterpolator.value(double x)	Interpolate value at a specified abscissa.
DerivativeStructure[]	HermiteInterpolator.value(DerivativeStructure x)	Interpolate value at a specified abscissa.

Constructors in org.apache.commons.math4.analysis.interpolation that throw NoDataException

Constructor	Description
BicubicInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY)
PiecewiseBicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f)
TricubicInterpolatingFunction(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.math4.analysis.polynomials

Methods in org.apache.commons.math4.analysis.polynomials that throw NoDataException

Modifier and Type	Method	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.
double	PolynomialFunction.Parametric.value(double x, double... parameters)	Compute the value of the function.
DerivativeStructure	PolynomialFunction.value(DerivativeStructure t)	Simple mathematical function.
protected static void	PolynomialFunctionNewtonForm.verifyInputArray(double[] a, double[] c)	Verifies that the input arrays are valid.

Constructors in org.apache.commons.math4.analysis.polynomials that throw NoDataException

Constructor	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.math4.analysis.solvers

Methods in org.apache.commons.math4.analysis.solvers that throw NoDataException

Modifier and Type	Method	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.math4.linear

Methods in org.apache.commons.math4.linear that throw NoDataException

Modifier and Type	Method	Description
protected void	AbstractFieldMatrix.checkSubMatrixIndex(int[] selectedRows, int[] selectedColumns)	Check if submatrix ranges indices are valid.
static void	MatrixUtils.checkSubMatrixIndex(AnyMatrix m, int[] selectedRows, int[] selectedColumns)	Check if submatrix ranges indices are valid.
void	AbstractFieldMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)	Copy a submatrix.
void	AbstractRealMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)	Copy a submatrix.
void	FieldMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)	Copy a submatrix.
void	RealMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] 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 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 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>	AbstractFieldMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Get a submatrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
FieldMatrix<T>	FieldMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Get a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
void	AbstractFieldMatrix.setSubMatrix(T[][] 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	Array2DRowFieldMatrix.setSubMatrix(T[][] subMatrix, int row, int column)	Replace the submatrix starting at (row, column) using data in the input subMatrix array.
void	Array2DRowRealMatrix.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	BlockRealMatrix.setSubMatrix(double[][] 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	RealMatrix.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.math4.linear that throw NoDataException

Constructor	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.math4.stat

Methods in org.apache.commons.math4.stat that throw NoDataException

Modifier and Type	Method	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.math4.stat.inference

Methods in org.apache.commons.math4.stat.inference that throw NoDataException

Modifier and Type	Method	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.
static double	InferenceTestUtils.pairedT(double[] sample1, double[] sample2)
double	TTest.pairedT(double[] sample1, double[] sample2)	Computes a paired, 2-sample t-statistic based on the data in the input arrays.
static double	InferenceTestUtils.pairedTTest(double[] sample1, double[] sample2)
static boolean	InferenceTestUtils.pairedTTest(double[] sample1, double[] sample2, double alpha)
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.
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.
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.math4.stat.regression

Methods in org.apache.commons.math4.stat.regression that throw NoDataException

Modifier and Type	Method	Description
RegressionResults	SimpleRegression.regress()	Performs a regression on data present in buffers and outputs a RegressionResults object.
RegressionResults	UpdatingMultipleLinearRegression.regress()	Performs a regression on data present in buffers and outputs a RegressionResults object

Uses of NoDataException in org.apache.commons.math4.util

Methods in org.apache.commons.math4.util that throw NoDataException

Modifier and Type	Method	Description
static double[]	MathArrays.convolve(double[] x, double[] h)	Calculates the convolution between two sequences.