org.ujmp.core.doublematrix.calculation.general.statistical

Interface StatisticalDoubleCalculations

All Known Subinterfaces:

BaseBigDecimalMatrix, BaseBigIntegerMatrix, BaseBooleanMatrix, BaseDoubleMatrix, BaseGenericMatrix<T>, BaseNumberMatrix<T>, BaseObjectMatrix, BigDecimalMatrix, BigDecimalMatrix2D, BigDecimalMatrixMultiD, BigIntegerMatrix, BigIntegerMatrix2D, BigIntegerMatrixMultiD, BooleanMatrix, BooleanMatrix2D, ByteArrayMatrix, ByteArrayMatrix2D, ByteMatrix, ByteMatrix2D, CanPerformCalculations, CharMatrix, CharMatrix2D, DenseBigDecimalMatrix, DenseBigDecimalMatrix2D, DenseBigDecimalMatrixMultiD, DenseBigIntegerMatrix, DenseBigIntegerMatrix2D, DenseBooleanMatrix, DenseBooleanMatrix2D, DenseByteArrayMatrix, DenseByteArrayMatrix2D, DenseByteMatrix, DenseByteMatrix2D, DenseCharMatrix, DenseCharMatrix2D, DenseDoubleMatrix, DenseDoubleMatrix2D, DenseDoubleMatrixMultiD, DenseFloatMatrix, DenseFloatMatrix2D, DenseGenericMatrix<T>, DenseGenericMatrix2D<T>, DenseGenericMatrixMultiD<T>, DenseIntMatrix, DenseIntMatrix2D, DenseLongMatrix, DenseLongMatrix2D, DenseMatrix, DenseMatrix2D, DenseMatrixMultiD, DenseNumberMatrix<T>, DenseNumberMatrix2D<T>, DenseNumberMatrixMultiD<T>, DenseObjectMatrix, DenseObjectMatrix2D, DenseObjectMatrixMultiD, DenseShortMatrix, DenseShortMatrix2D, DenseStringMatrix, DenseStringMatrix2D, DoubleCalculations, DoubleMatrix, DoubleMatrix2D, DoubleMatrixMultiD, FileOrDirectoryMatrix, FloatMatrix, FloatMatrix2D, GeneralDoubleCalculations, GenericMatrix<T>, GenericMatrix2D<T>, GenericMatrixMultiD<T>, GraphMatrix<N,E>, IntMatrix, IntMatrix2D, ListDataSet, ListMatrix<T>, LongMatrix, LongMatrix2D, MapMatrix<K,V>, Matrix, Matrix2D, MatrixMultiD, NumberMatrix<T>, NumberMatrix2D<T>, NumberMatrixMultiD<T>, ObjectMatrix, ObjectMatrix2D, ObjectMatrixMultiD, Sample, SetMatrix<A>, ShortMatrix, ShortMatrix2D, SparseBigDecimalMatrix, SparseBigDecimalMatrix2D, SparseBigDecimalMatrixMultiD, SparseBigIntegerMatrix, SparseBigIntegerMatrix2D, SparseBooleanMatrix, SparseBooleanMatrix2D, SparseByteArrayMatrix, SparseByteArrayMatrix2D, SparseByteMatrix, SparseByteMatrix2D, SparseCharMatrix, SparseCharMatrix2D, SparseDoubleMatrix, SparseDoubleMatrix2D, SparseDoubleMatrixMultiD, SparseFloatMatrix, SparseFloatMatrix2D, SparseGenericMatrix<T>, SparseGenericMatrix2D<T>, SparseGenericMatrixMultiD<T>, SparseIntMatrix, SparseIntMatrix2D, SparseLongMatrix, SparseLongMatrix2D, SparseMatrix, SparseMatrix2D, SparseMatrixMultiD, SparseNumberMatrix<T>, SparseNumberMatrix2D<T>, SparseNumberMatrixMultiD<T>, SparseObjectMatrix, SparseObjectMatrix2D, SparseObjectMatrixMultiD, SparseShortMatrix, SparseShortMatrix2D, SparseStringMatrix, SparseStringMatrix2D, StringMatrix, StringMatrix2D, TextBlock, TextSentence, TextToken, TreeMatrix<T>, Variable

All Known Implementing Classes:

AbstractBigDecimalMatrix, AbstractBigIntegerMatrix, AbstractBooleanMatrix, AbstractByteArrayMatrix, AbstractByteMatrix, AbstractCharMatrix, AbstractDenseBigDecimalMatrix, AbstractDenseBigDecimalMatrix2D, AbstractDenseBigIntegerMatrix, AbstractDenseBigIntegerMatrix2D, AbstractDenseBooleanMatrix, AbstractDenseBooleanMatrix2D, AbstractDenseByteArrayMatrix, AbstractDenseByteArrayMatrix2D, AbstractDenseByteMatrix, AbstractDenseByteMatrix2D, AbstractDenseCharMatrix, AbstractDenseCharMatrix2D, AbstractDenseDoubleMatrix2D, AbstractDenseDoubleMatrixMultiD, AbstractDenseFloatMatrix, AbstractDenseFloatMatrix2D, AbstractDenseGenericMatrix, AbstractDenseGenericMatrix2D, AbstractDenseIntMatrix, AbstractDenseIntMatrix2D, AbstractDenseLongMatrix, AbstractDenseLongMatrix2D, AbstractDenseObjectMatrix, AbstractDenseObjectMatrix2D, AbstractDenseShortMatrix, AbstractDenseShortMatrix2D, AbstractDenseStringMatrix, AbstractDenseStringMatrix2D, AbstractDoubleMatrix, AbstractDoubleMatrix2D, AbstractDoubleMatrixMultiD, AbstractFloatMatrix, AbstractGenericMatrix, AbstractGraphMatrix, AbstractIntMatrix, AbstractListDataSet, AbstractListMatrix, AbstractLongMatrix, AbstractMapMatrix, AbstractMapMatrixList, AbstractMapToSparseMatrixWrapper, AbstractMapToTiledMatrix2DWrapper, AbstractMatrix, AbstractNumberMatrix, AbstractObjectMatrix, AbstractSample, AbstractSetMatrix, AbstractShortMatrix, AbstractSparseBigDecimalMatrix, AbstractSparseBigDecimalMatrix2D, AbstractSparseBigIntegerMatrix, AbstractSparseBigIntegerMatrix2D, AbstractSparseBooleanMatrix, AbstractSparseBooleanMatrix2D, AbstractSparseByteArrayMatrix, AbstractSparseByteArrayMatrix2D, AbstractSparseByteMatrix, AbstractSparseByteMatrix2D, AbstractSparseCharMatrix, AbstractSparseCharMatrix2D, AbstractSparseDoubleMatrix, AbstractSparseDoubleMatrix2D, AbstractSparseFloatMatrix, AbstractSparseFloatMatrix2D, AbstractSparseGenericMatrix, AbstractSparseGenericMatrix2D, AbstractSparseIntMatrix, AbstractSparseIntMatrix2D, AbstractSparseLongMatrix, AbstractSparseLongMatrix2D, AbstractSparseObjectMatrix, AbstractSparseObjectMatrix2D, AbstractSparseShortMatrix, AbstractSparseShortMatrix2D, AbstractSparseStringMatrix, AbstractSparseStringMatrix2D, AbstractStringMatrix, AbstractTreeMatrix, AbstractVariable, ArrayDenseBigDecimalMatrix2D, ArrayDenseBigIntegerMatrix2D, ArrayDenseBooleanMatrix2D, ArrayDenseByteMatrix2D, ArrayDenseCharMatrix2D, ArrayDenseDoubleMatrix2D, ArrayDenseFloatMatrix2D, ArrayDenseIntMatrix2D, ArrayDenseLongMatrix2D, ArrayDenseObjectMatrix2D, ArrayDenseShortMatrix2D, ArrayDenseStringMatrix2D, AvailableProcessorsMatrix, BenchmarkConfig, BigDecimalCalculationMatrix, BigIntegerCalculationMatrix, BitSetDenseBooleanMatrix2D, BlockDenseDoubleMatrix2D, BooleanCalculationMatrix, BufferedObjectMatrix, ByteCalculationMatrix, CharCalculationMatrix, ClientMatrix, DefaultDenseBigDecimalMatrix2D, DefaultDenseBigIntegerMatrix2D, DefaultDenseByteMatrix2D, DefaultDenseCharMatrix2D, DefaultDenseDoubleMatrix2D, DefaultDenseDoubleMatrixMultiD, DefaultDenseFloatMatrix2D, DefaultDenseGenericMatrix2D, DefaultDenseIntMatrix2D, DefaultDenseLongMatrix2D, DefaultDenseObjectMatrix2D, DefaultDenseObjectMatrixMultiD, DefaultDenseShortMatrix2D, DefaultDenseStringMatrix2D, DefaultGraphMatrix, DefaultListDataSet, DefaultListMatrix, DefaultMapMatrix, DefaultSample, DefaultSetMatrix, DefaultSparseBigDecimalMatrix, DefaultSparseBigIntegerMatrix, DefaultSparseBooleanMatrix, DefaultSparseByteMatrix, DefaultSparseCharMatrix, DefaultSparseColumnObjectMatrix2D, DefaultSparseDoubleMatrix, DefaultSparseDoubleVector1D, DefaultSparseFloatMatrix, DefaultSparseGenericMatrix, DefaultSparseIntMatrix, DefaultSparseLongMatrix, DefaultSparseObjectMatrix, DefaultSparseRowDoubleMatrix2D, DefaultSparseRowObjectMatrix2D, DefaultSparseShortMatrix, DefaultSparseStringMatrix, DefaultTextBlock, DefaultTextSentence, DefaultTextToken, DefaultTiledObjectMatrix2D, DefaultTreeMatrix, DefaultVariable, DenseCSVStringMatrix2D, DenseFileMatrix, DirectoryMatrix, DoubleCalculationMatrix, EmptyMatrix, FileFormatMatrix, FileMatrix, FloatCalculationMatrix, HttpMatrix, ImageMatrix, IndexedSparseDoubleMatrix2D, IntCalculationMatrix, IrisMatrix, JDMPPluginsMatrix, LocalhostMatrix, LogMatrix, LongCalculationMatrix, MandelbrotMatrix, MatrixDataSet, MatrixLibraries, MatrixListToMatrixWrapper, MatrixSample, MatrixUIDefaults, MemoryUsageMatrix, MortonDenseDoubleMartrix2D, NetworkInterfaceMatrix, NetworkMatrix, ObjectCalculationMatrix, ObjectTreeMatrix, OperatingSystemMatrix, RandomSeedMatrix, RelationalSample, RemoteHostMatrix, RemoteObjectMatrixUDP, RunningThreadsMatrix, SerializedSparseObjectMatrix, ServerObjectMatrixUDP, ShortCalculationMatrix, SparseCSVMatrix, SparseFeatureVector, StringCalculationMatrix, SubnetMatrix, SynchronizedGenericMatrix, SystemEnvironmentMatrix, SystemPropertiesMatrix, SystemTimeMatrix, TextContentMatrix, TimeSeriesMatrix, UJMPPluginsMatrix, UJMPSettings, VolatileSparseObjectMatrix, WaveMatrix, WelcomeMatrix, ZipEntryMatrix, ZipFileMatrix

public interface StatisticalDoubleCalculations

Method Summary

Modifier and Type	Method and Description
Matrix	corrcoef(Calculation.Ret returnType, boolean ignoreNaN, boolean besselsCorrection) Calculates the Pearson correlation.
Matrix	cov(Calculation.Ret returnType, boolean ignoreNaN, boolean besselsCorrection) Calculates the covariance Matrix.
Matrix	cumprod(boolean ignoreNaN)
Matrix	cumsum(boolean ignoreNaN)
Matrix	diff(Calculation.Ret returnType, int dimension, boolean ignoreNaN)
Matrix	indexOfMax(Calculation.Ret returnType, int dimension) Finds the index of the maximum value in the matrix
Matrix	indexOfMin(Calculation.Ret returnType, int dimension) Finds the index of the minimum value in the matrix
Matrix	max(Calculation.Ret returnType, int dimension) Calculates the maximum of the values in the matrix either rowwise, columnwise, or global.
Matrix	mean(Calculation.Ret returnType, int dimension, boolean ignoreNaN) Calculates the mean of all entries in the Matrix either per row, per column, or global.
Matrix	min(Calculation.Ret returnType, int dimension) Calculates the mimimum of the values in the matrix either rowwise, columnwise, or global.
Matrix	mutualInf(Calculation.Ret returnType) Calculates the mutual information.
Matrix	pairedTTest(Calculation.Ret returnType) Calculates a paired T-Test on the matrix.
Matrix	prod(Calculation.Ret returnType, int dimension, boolean ignoreNaN)
Matrix	std(Calculation.Ret returnType, int dimension, boolean ignoreNaN, boolean besselsCorrection) Calculates the standard deviation of all entries in the Matrix either per row, per column, or global.
Matrix	sum(Calculation.Ret returnType, int dimension, boolean ignoreNaN) Calculates the sum of all entries in the Matrix either per row, per column, or global.
Matrix	var(Calculation.Ret returnType, int dimension, boolean ignoreNaN, boolean besselsCorrection) Calculates the variance of all entries in the Matrix either per row, per column, or global.

Method Detail

diff

Matrix diff(Calculation.Ret returnType,
            int dimension,
            boolean ignoreNaN)

prod

Matrix prod(Calculation.Ret returnType,
            int dimension,
            boolean ignoreNaN)

cumsum

Matrix cumsum(boolean ignoreNaN)

cumprod

Matrix cumprod(boolean ignoreNaN)

min

Matrix min(Calculation.Ret returnType,
           int dimension)

Calculates the mimimum of the values in the matrix either rowwise, columnwise, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - the axis along which should be calculated, e.g. ROW=0, COLUMN=1 or ALL

Returns:

A new matrix containing the minimum values

max

Matrix max(Calculation.Ret returnType,
           int dimension)

Calculates the maximum of the values in the matrix either rowwise, columnwise, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - the axis along which should be calculated, e.g. ROW=0, COLUMN=1 or ALL

Returns:

A new matrix containing the maximum values

sum

Matrix sum(Calculation.Ret returnType,
           int dimension,
           boolean ignoreNaN)

Calculates the sum of all entries in the Matrix either per row, per column, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

ignoreNaN - should missing values be ignored

Returns:

Matrix with the sum of the values along the desired axis

mean

Matrix mean(Calculation.Ret returnType,
            int dimension,
            boolean ignoreNaN)

Calculates the mean of all entries in the Matrix either per row, per column, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

ignoreNaN - should missing values be ignored

Returns:

Matrix with the sum of the values along the desired axis

var

Matrix var(Calculation.Ret returnType,
           int dimension,
           boolean ignoreNaN,
           boolean besselsCorrection)

Calculates the variance of all entries in the Matrix either per row, per column, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

ignoreNaN - should missing values be ignored

besselsCorrection - use (n-1) instead of n

Returns:

Matrix with the sum of the values along the desired axis

std

Matrix std(Calculation.Ret returnType,
           int dimension,
           boolean ignoreNaN,
           boolean besselsCorrection)

Calculates the standard deviation of all entries in the Matrix either per row, per column, or global.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

ignoreNaN - should missing values be ignored

besselsCorrection - use (n-1) instead of n

Returns:

Matrix with the sum of the values along the desired axis

cov

Matrix cov(Calculation.Ret returnType,
           boolean ignoreNaN,
           boolean besselsCorrection)

Calculates the covariance Matrix. Each row is an observation and each column is a variable.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

ignoreNaN - should missing values be ignored

besselsCorrection - use (n-1) instead of n

Returns:

Covariance Matrix

corrcoef

Matrix corrcoef(Calculation.Ret returnType,
                boolean ignoreNaN,
                boolean besselsCorrection)

Calculates the Pearson correlation. Each row is an observation and each column is a variable.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

ignoreNaN - should missing values be ignored

besselsCorrection - use (n-1) instead of n

Returns:

Covariance Matrix

mutualInf

Matrix mutualInf(Calculation.Ret returnType)

Calculates the mutual information. Each row is an observation and each column is a variable.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

Returns:

Matrix with mutual information

pairedTTest

Matrix pairedTTest(Calculation.Ret returnType)

Calculates a paired T-Test on the matrix. Each row is an observation and each column is a variable.

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

Returns:

Matrix with p-values of the T-Test

indexOfMax

Matrix indexOfMax(Calculation.Ret returnType,
                  int dimension)

Finds the index of the maximum value in the matrix

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

Returns:

Matrix containing the coordinates of the Maximum

indexOfMin

Matrix indexOfMin(Calculation.Ret returnType,
                  int dimension)

Finds the index of the minimum value in the matrix

Parameters:

returnType - Select whether a new or a linked Matrix is returned, or if the operation is performed on the original Matrix

dimension - The axis along which to calculate

Returns:

Matrix containing the coordinates of the Minimum