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Packages that use NoDataException | |
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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 |
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Constructors in org.apache.commons.math3.analysis.function that throw NoDataException | |
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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 |
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Methods in org.apache.commons.math3.analysis.interpolation that throw NoDataException | |
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PolynomialFunction[] |
HermiteInterpolator.getPolynomials()
Compute the interpolation polynomials. |
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 |
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. |
BivariateFunction |
BivariateGridInterpolator.interpolate(double[] xval,
double[] yval,
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. |
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. |
DerivativeStructure[] |
HermiteInterpolator.value(DerivativeStructure x)
Interpolate value at a specified abscissa. |
double[] |
HermiteInterpolator.value(double x)
Interpolate value at a specified abscissa. |
Constructors in org.apache.commons.math3.analysis.interpolation that throw NoDataException | |
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BicubicSplineInterpolatingFunction(double[] x,
double[] y,
double[][] f,
double[][] dFdX,
double[][] dFdY,
double[][] d2FdXdY)
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MicrosphereInterpolatingFunction(double[][] xval,
double[] yval,
int brightnessExponent,
int microsphereElements,
UnitSphereRandomVectorGenerator rand)
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TricubicSplineInterpolatingFunction(double[] x,
double[] y,
double[] z,
double[][][] f,
double[][][] dFdX,
double[][][] dFdY,
double[][][] dFdZ,
double[][][] d2FdXdY,
double[][][] d2FdXdZ,
double[][][] d2FdYdZ,
double[][][] d3FdXdYdZ)
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Uses of NoDataException in org.apache.commons.math3.analysis.polynomials |
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Methods in org.apache.commons.math3.analysis.polynomials that throw NoDataException | |
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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. |
DerivativeStructure |
PolynomialFunction.value(DerivativeStructure t)
Simple mathematical function. |
Constructors in org.apache.commons.math3.analysis.polynomials that throw NoDataException | |
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PolynomialFunction(double[] c)
Construct a polynomial with the given coefficients. |
Uses of NoDataException in org.apache.commons.math3.analysis.solvers |
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Methods in org.apache.commons.math3.analysis.solvers that throw NoDataException | |
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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 |
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Methods in org.apache.commons.math3.complex that throw NoDataException | |
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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 | |
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ComplexFormat(String imaginaryCharacter)
Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts. |
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ComplexFormat(String imaginaryCharacter,
NumberFormat format)
Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts. |
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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 |
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Constructors in org.apache.commons.math3.filter that throw NoDataException | |
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DefaultMeasurementModel(double[][] measMatrix,
double[][] measNoise)
Create a new MeasurementModel , taking double arrays as input parameters for the
respective measurement matrix and noise. |
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DefaultProcessModel(double[][] stateTransition,
double[][] control,
double[][] processNoise)
Create a new ProcessModel , taking double arrays as input parameters. |
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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 |
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Methods in org.apache.commons.math3.linear that throw NoDataException | ||
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static void |
MatrixUtils.checkSubMatrixIndex(AnyMatrix m,
int[] selectedRows,
int[] selectedColumns)
Check if submatrix ranges indices are valid. |
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protected void |
AbstractFieldMatrix.checkSubMatrixIndex(int[] selectedRows,
int[] selectedColumns)
Check if submatrix ranges indices are valid. |
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void |
AbstractRealMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
double[][] destination)
Copy a submatrix. |
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void |
RealMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
double[][] destination)
Copy a submatrix. |
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void |
FieldMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
T[][] destination)
Copy a submatrix. |
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void |
AbstractFieldMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
T[][] destination)
Copy a submatrix. |
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static
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MatrixUtils.createColumnFieldMatrix(T[] columnData)
Creates a column FieldMatrix using the data from the input
array. |
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static RealMatrix |
MatrixUtils.createColumnRealMatrix(double[] columnData)
Creates a column RealMatrix using the data from the input
array. |
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static
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MatrixUtils.createFieldMatrix(T[][] data)
Returns a FieldMatrix whose entries are the the values in the
the input array. |
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static
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MatrixUtils.createFieldVector(T[] data)
Creates a FieldVector using the data from the input array. |
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static RealMatrix |
MatrixUtils.createRealMatrix(double[][] data)
Returns a RealMatrix whose entries are the the values in the
the input array. |
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static RealVector |
MatrixUtils.createRealVector(double[] data)
Creates a RealVector using the data from the input array. |
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static
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MatrixUtils.createRowFieldMatrix(T[] rowData)
Create a row FieldMatrix using the data from the input
array. |
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static RealMatrix |
MatrixUtils.createRowRealMatrix(double[] rowData)
Create a row RealMatrix using the data from the input
array. |
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protected static
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AbstractFieldMatrix.extractField(T[] d)
Get the elements type from an array. |
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protected static
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AbstractFieldMatrix.extractField(T[][] d)
Get the elements type from an array. |
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RealMatrix |
AbstractRealMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Gets a submatrix. |
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RealMatrix |
RealMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Gets a submatrix. |
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FieldMatrix<T> |
FieldMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Get a submatrix. |
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FieldMatrix<T> |
AbstractFieldMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Get a submatrix. |
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void |
Array2DRowRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
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void |
AbstractRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
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void |
RealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
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void |
BlockRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
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void |
FieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
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void |
Array2DRowFieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
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void |
AbstractFieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
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void |
BlockFieldMatrix.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 | |
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Array2DRowFieldMatrix(Field<T> field,
T[][] d)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
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Array2DRowFieldMatrix(Field<T> field,
T[][] d,
boolean copyArray)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
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Array2DRowFieldMatrix(T[] v)
Create a new (column) FieldMatrix<T> using v as the
data for the unique column of the created matrix. |
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Array2DRowFieldMatrix(T[][] d)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
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Array2DRowFieldMatrix(T[][] d,
boolean copyArray)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
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Array2DRowRealMatrix(double[][] d)
Create a new RealMatrix using the input array as the underlying
data array. |
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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 |
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Methods in org.apache.commons.math3.stat that throw NoDataException | |
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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 |
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Methods in org.apache.commons.math3.stat.inference that throw NoDataException | |
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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 |
TestUtils.pairedT(double[] sample1,
double[] sample2)
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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.pairedTTest(double[] sample1,
double[] sample2)
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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 boolean |
TestUtils.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
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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.math3.stat.regression |
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Methods in org.apache.commons.math3.stat.regression that throw NoDataException | |
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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 |
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