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

Packages that use NoDataException
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 and confidence interval construction. 
org.apache.commons.math3.stat.regression Statistical routines involving multivariate data. 
 

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

Constructors in org.apache.commons.math3.analysis.function that throw NoDataException
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
 T[][] FieldHermiteInterpolator.derivatives(T x, int order)
          Interpolate value and first derivatives at a specified abscissa.
 PolynomialFunction[] HermiteInterpolator.getPolynomials()
          Compute the interpolation polynomials.
 MultivariateFunction MultivariateInterpolator.interpolate(double[][] xval, double[] yval)
          Computes an interpolating function for the data set.
 MultivariateFunction MicrosphereInterpolator.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.
 BicubicSplineInterpolatingFunction BicubicSplineInterpolator.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.
 BicubicSplineInterpolatingFunction SmoothingPolynomialBicubicSplineInterpolator.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
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
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
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
 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
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
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
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
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.
 RealMatrix AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)
          Gets a submatrix.
 RealMatrix RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)
          Gets a submatrix.
 FieldMatrix<T> AbstractFieldMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)
          Get a submatrix.
 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 BlockRealMatrix.setSubMatrix(double[][] 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 FieldMatrix.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.
 void BlockFieldMatrix.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.
 

Constructors in org.apache.commons.math3.linear that throw NoDataException
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
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
 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
 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.
 



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