A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

T

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.diagonalization.Tridiagonalization

Get a copy of the T matrix, such that T = Q %*% A %*% Q T is triangular.

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.QRAlgorithm

Get a copy of the T matrix as in the real Schur canonical form Q'MQ = T T is quasi upper triangular.

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.gaussianelimination.GaussianElimination

Get a copy of the transformation matrix, T, such that T %*% A == U

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.gaussianelimination.GaussJordanElimination

Get the transformation matrix, T, such that T %*% A == U

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.ImmutableMatrix

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.linearsystem.Kernel

Get the transformation matrix, T, such that T %*% A == U To find a particular solution for a non-homogeneous system of linear equations with the same A, i.e., Ax = b we do x = T %*% b where x is a particular solution.

t() - Method in interface com.numericalmethod.suanshu.matrix.doubles.MatrixRing

t(this) Compute the transpose of this matrix.

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.BidiagonalMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.DiagonalMatrix

The transpose of a diagonal matrix is the same as itself.

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.TridiagonalMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.LowerTriangularMatrix

t(A)

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.SymmetricMatrix

t(A) = A.

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.UpperTriangularMatrix

t(A)

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.GivensMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.MatrixMathImpl

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.PermutationMatrix

The transpose of a permutation matric is the same as its inverse.

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.CsrSparseMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.DokSparseMatrix

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.LilSparseMatrix

T() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.ElementaryOperation

Get a copy of the transformation matrix T.

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.ImmutableKroneckerProduct

t() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.SubMatrixRef

t - Variable in class com.numericalmethod.suanshu.stats.descriptive.rank.Rank

t = Σ(t_i³ - t_i)

t - Variable in class com.numericalmethod.suanshu.stats.regression.linear.ols.Beta

the z- or t-value for the regression coefficients β^

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.integration.sde.RandomWalk.Iterator

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.MultiVariateRealization.Iterator

Get the current timestamp of the realization.

t() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.FtWt

Get the current time.

T - Variable in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.EvenlySpacedGrid

the ending of the time interval

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.EvenlySpacedGrid

the i-th time point in the time grid discretization

T() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.EvenlySpacedGrid

t(int) - Method in interface com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.TimeGrid

the i-th time point in the time grid discretization

T() - Method in interface com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.TimeGrid

the last time point available

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.UnitGrid

the i-th time point in the time grid discretization

T() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.UnitGrid

T(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.Filtration

Get the t-th time point.

T() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.Filtration

Get the entire time grid.

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde.PathByIdImpl

the pos-th time point in the time grid discretization

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde.RandomWalk.Iterator

t(int) - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.Realization.Iterator

Get the current timestamp of the realization.

t() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.sde.FtWt

Get the current time.

T - Class in com.numericalmethod.suanshu.stats.test.mean

Student's TDistribution-test tests for the equality of means, for the one-sample case, against a hypothetical mean, and for two-sample case, of two populations.

T(double[], double) - Constructor for class com.numericalmethod.suanshu.stats.test.mean.T

Construct a one-sample location test of whether the mean of a normally distributed population has a value specified in a null hypothesis.

T(double[], double[]) - Constructor for class com.numericalmethod.suanshu.stats.test.mean.T

Construct Welch's t test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.

T(double[], double[], double) - Constructor for class com.numericalmethod.suanshu.stats.test.mean.T

Construct Welch's t test, an adaptation of Student's t-test, for the use with two samples having possibly unequal variances.

T(double[], double[], boolean, double) - Constructor for class com.numericalmethod.suanshu.stats.test.mean.T

Construct a two sample location test of the null hypothesis that the means of two normally distributed populations are equal.

T - Variable in class com.numericalmethod.suanshu.stats.test.mean.T

the associated TDistribution distribution

T0 - Variable in class com.numericalmethod.suanshu.stats.stochasticprocess.timepoints.EvenlySpacedGrid

the beginning of the time interval

t0 - Variable in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.Expectation

the beginning time of the integral time interval

t1 - Variable in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.Expectation

the ending time of the integral time interval

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.DoubleExponential

Get the lower limit of the integral.

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.Exponential

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.InvertingVariable

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.NoChangeOfVariable

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.PowerLawSingularity

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.StandardInterval

ta() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.Substitution

Get the lower limit of the integral.

table() - Method in class com.numericalmethod.suanshu.analysis.interpolation.NevilleTable

Get a copy of the Neville table.

Tableau - Class in com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex

This class implements a "tableau" and its operations used in the Simplex method when solving an LP problem.

Tableau(Tableau.Label[], Tableau.Label[], Matrix, double) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau

Construct a simplex tableau.

Tableau(Matrix, double) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau

Construct a simplex tableau, assuming the standard form.

Tableau(StandardLpProblem2) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau

Construct a simplex tableau from a standard problem.

Tableau(Tableau) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau

Copy ctor.

Tableau.Label - Class in com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex

Tableau.Label(Tableau.LabelType, int) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau.Label

Tableau.LabelType - Enum in com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex

tallR() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.qr.GramSchmidt

tallR() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.qr.HouseholderReflection

tallR() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.qr.QR

tallR() - Method in interface com.numericalmethod.suanshu.matrix.doubles.factorization.qr.QRDecomposition

Get a copy of the tall R matrix.

tan(Complex) - Static method in class com.numericalmethod.suanshu.number.complex.ElementaryFunction

Tangent of a complex number (a + bi).

tanh(Complex) - Static method in class com.numericalmethod.suanshu.number.complex.ElementaryFunction

Hyperbolic tangent of a complex number (a + bi).

tau - Variable in class com.numericalmethod.suanshu.optimization.unconstrained.linesearch.Fletcher

parameter tau ensures that the result is not too close to the boundary

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.DoubleExponential

Get the upper limit of the integral.

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.Exponential

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.InvertingVariable

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.NoChangeOfVariable

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.PowerLawSingularity

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.StandardInterval

tb() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.Substitution

Get the upper limit of the integral.

TDistribution - Class in com.numericalmethod.suanshu.stats.distribution.univariate

Student's t distribution is the probability distribution of t, where x̄ - μ t = ------------ s / sqrt(N) x̄ is the sample mean; μ is the population mean; s is the square root of the sample variance; N is the sample size; The importance of the Student's distribution is when (as in nearly all practical statistical work) the population standard deviation is unknown and has to be estimated from the data.

TDistribution(double) - Constructor for class com.numericalmethod.suanshu.stats.distribution.univariate.TDistribution

Construct a Student's t distribution.

term - Variable in class com.numericalmethod.suanshu.analysis.sequence.Summation

the terms to sum up in a series It takes an index, and computes a value;

test(double) - Method in interface com.numericalmethod.suanshu.misc.R.ifelse

Decide whether x satisfies the if part of the statement.

test - Variable in class com.numericalmethod.suanshu.stats.cointegration.CointegrationMle

the type of Johansen test

testStatistics - Variable in class com.numericalmethod.suanshu.stats.test.HypothesisTest

the test statistics

testStatistics() - Method in class com.numericalmethod.suanshu.stats.test.HypothesisTest

Get the test statistics.

testStatistics() - Method in class com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity.BreuschPagan

testStatistics() - Method in class com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity.White

theta - Variable in class com.numericalmethod.suanshu.optimization.unconstrained.quasinewton.Huang

θ, a Huang family parameterization

theta - Variable in class com.numericalmethod.suanshu.stats.distribution.univariate.GammaDistribution

the scale parameter

theta(double) - Method in class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.Binomial

The canonical parameter of the distribution in terms of the mean μ.

theta(double) - Method in interface com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.ExponentialDistribution

The canonical parameter of the distribution in terms of the mean μ.

theta(double) - Method in class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.Gamma

theta(double) - Method in class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.Gaussian

theta(double) - Method in class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.InverseGaussian

theta(double) - Method in class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.Poisson

theta - Variable in class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.ArimaxModel

the MA coefficients

threshold - Variable in class com.numericalmethod.suanshu.analysis.sequence.Summation

the convergence threshold for a convergent series When a term falls below this threshold, the summing process stops.

threshold - Variable in class com.numericalmethod.suanshu.stats.regression.linear.glm.IWLS

the convergence threshold

throwIfDifferentDimension(MatrixDimension, MatrixDimension) - Static method in class com.numericalmethod.suanshu.matrix.DimensionCheck

Throws if A1.nrow !

throwIfIncompatible4Multiplication(MatrixDimension, MatrixDimension) - Static method in class com.numericalmethod.suanshu.matrix.DimensionCheck

Throws if A1.ncol !

throwIfIncompatible4Multiplication(MatrixDimension, Vector) - Static method in class com.numericalmethod.suanshu.matrix.DimensionCheck

Throws if A.ncol !

throwIfInvalidColumn(MatrixDimension, int) - Static method in class com.numericalmethod.suanshu.matrix.DimensionCheck

Throws if accessing an out of range column.

throwIfInvalidRow(MatrixDimension, int) - Static method in class com.numericalmethod.suanshu.matrix.DimensionCheck

Throws if accessing an out of range row.

time(int) - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.GenericTimeTimeSeries

Get the time at position index.

time - Variable in class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Entry

the time index, timestamp

time(int) - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.GenericTimeTimeSeries

Get the time at position index.

TimeGrid - Interface in com.numericalmethod.suanshu.stats.stochasticprocess.timepoints

This interface represents the discrete time points in [t1, tn = T] for a stochastic process.

TimeInterval - Class in com.numericalmethod.suanshu.time

This class represents a time interval.

TimeInterval(ComparableDateTime, ComparableDateTime) - Constructor for class com.numericalmethod.suanshu.time.TimeInterval

Construct a time interval from two time points.

TimeInterval(DateTime, DateTime) - Constructor for class com.numericalmethod.suanshu.time.TimeInterval

Construct a time interval from two time points.

TimeIntervals - Class in com.numericalmethod.suanshu.time

TimeIntervals() - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

TimeIntervals(ComparableDateTime, ComparableDateTime) - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

TimeIntervals(DateTime, DateTime) - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

TimeIntervals(Interval<ComparableDateTime>) - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

TimeIntervals(Interval<ComparableDateTime>...) - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

TimeIntervals(Intervals<ComparableDateTime>) - Constructor for class com.numericalmethod.suanshu.time.TimeIntervals

timePoints - Variable in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde.PathByIdImpl

the set of discretized time points

TimeSeries<T,V> - Interface in com.numericalmethod.suanshu.stats.timeseries

A time series is an serially indexed collection of items.

TimeSeries - Interface in com.numericalmethod.suanshu.stats.timeseries.univariate.realtime

This represents a univariate time series indexed by integers.

TimeSeries<T> - Interface in com.numericalmethod.suanshu.stats.timeseries.univariate

This represents a univariate time series indexed by some notion of time.

TimeSeries.Entry<T,V> - Class in com.numericalmethod.suanshu.stats.timeseries

A time series is composed of a sequence of Entrys.

TimeSeries.Entry(T, V) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Entry

Construct an entry from a time-value pair.

TimeSeries.Entry - Class in com.numericalmethod.suanshu.stats.timeseries.univariate.realtime

the TimeSeries.Entry for an integer-indexed univariate time series

TimeSeries.Entry(int, double) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.TimeSeries.Entry

TimeSeries.Entry<T> - Class in com.numericalmethod.suanshu.stats.timeseries.univariate

the TimeSeries.Entry for a univariate time series

TimeSeries.Entry(T, double) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.univariate.TimeSeries.Entry

TimeSeries.Iterator<E extends TimeSeries.Entry<?,?>> - Class in com.numericalmethod.suanshu.stats.timeseries

the Iterator to read a time series This class provides a default implementation of an Iterator for subclasses to override.

TimeSeries.Iterator(TimeSeries<?, ?>) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Iterator

Construct an iterator to read a time series.

TimeSeries.Iterator - Class in com.numericalmethod.suanshu.stats.timeseries.univariate.realtime

the Iterator to read an integer-indexed univariate time series

TimeSeries.Iterator(TimeSeries) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.TimeSeries.Iterator

TimeSeries.Iterator<E extends TimeSeries.Entry<?>> - Class in com.numericalmethod.suanshu.stats.timeseries.univariate

the Iterator to read a univariate time series

TimeSeries.Iterator(TimeSeries<?>) - Constructor for class com.numericalmethod.suanshu.stats.timeseries.univariate.TimeSeries.Iterator

timestamps() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.GenericTimeTimeSeries

Get all the timestamps.

timestamps() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.GenericTimeTimeSeries

Get all the timestamps.

to1DArray(DenseMatrix) - Static method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrixUtils

Get all matrix entries in the form of a 1D double[] array.

to1DArray(Matrix) - Static method in class com.numericalmethod.suanshu.matrix.doubles.operation.MatrixUtils

Get all matrix entries in the form of a 1D double[] array.

to2DArray(DenseMatrix) - Static method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrixUtils

Get all matrix entries in the form of a 2D double[][] array.

to2DArray(Matrix) - Static method in class com.numericalmethod.suanshu.matrix.doubles.operation.MatrixUtils

Get all matrix entries in the form of a 2D double[][] array.

toArray() - Method in class com.numericalmethod.suanshu.datastructure.list.VectorList

Get an array of all the elements in this list.

toArray() - Method in class com.numericalmethod.suanshu.datastructure.MathTable.Row

Convert the row to a double array, double[], excluding the index.

toArray() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseVector

toArray(int) - Method in class com.numericalmethod.suanshu.signalprocessing.Innovations

Get a copy of the (truncated) innovations.

toArray() - Method in class com.numericalmethod.suanshu.signalprocessing.Innovations

Get a copy of the innovations.

toArray() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde.RandomWalk.Realization

toArray() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.GenericTimeTimeSeries

toArray() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.GenericTimeTimeSeries

toArray() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.OneDimensionTimeSeries

toArray() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.SimpleTimeSeries

toArray() - Method in interface com.numericalmethod.suanshu.stats.timeseries.univariate.TimeSeries

Convert this time series into an array.

toArray() - Method in class com.numericalmethod.suanshu.vector.doubles.dense.DenseVector

toArray() - Method in class com.numericalmethod.suanshu.vector.doubles.ImmutableVector

toArray() - Method in interface com.numericalmethod.suanshu.vector.doubles.Vector

Get a copy of all vector entries in the form of a 1D double[] array.

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrix

toDense() - Method in interface com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.Densifiable

Densify a matrix, i.e., convert a matrix implementation to a standard dense matrix, DenseMatrix.

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.LowerTriangularMatrix

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.SymmetricMatrix

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.UpperTriangularMatrix

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.CsrSparseMatrix

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.DokSparseMatrix

toDense() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.LilSparseMatrix

toDouble() - Method in class com.numericalmethod.suanshu.number.complex.Complex

Cast the complex number to a Double if it is a real number.

toElementList() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.CsrSparseMatrix

toElementList() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.DokSparseMatrix

toElementList() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.LilSparseMatrix

toElementList() - Method in interface com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseMatrix

Export the non-zero values in the matrix as a list of SparseElements.

TOKYO - Static variable in class com.numericalmethod.suanshu.time.JodaTimeUtils

Tokyo

tol - Variable in class com.numericalmethod.suanshu.analysis.uniroot.Uniroot

the convergence criterion such that the search succeeds when |f(x)| < tol

tol - Variable in class com.numericalmethod.suanshu.optimization.unconstrained.linesearch.Fletcher

the convergence tolerance

tol - Variable in class com.numericalmethod.suanshu.optimization.unconstrained.steepestdescent.SteepestDescent

the convergence tolerance

tol - Variable in class com.numericalmethod.suanshu.optimization.univariate.BracketSearch

the convergence tolerance It should be no less than the square root of the machine precision.

tolerance(Tolerance) - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.IterativeSolver.Problem

Override the tolerance instance.

tolerance() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.IterativeSolver.Problem

Get the specified Tolerance instance.

Tolerance - Interface in com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative

The tolerance criteria for the iterative algorithm to stop.

toMatrix() - Method in class com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.integration.sde.RandomWalk.MultiVariateRealization

toMatrix() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.GenericTimeTimeSeries

toMatrix() - Method in interface com.numericalmethod.suanshu.stats.timeseries.multivariate.MultiVariateTimeSeries

Convert this multivariate time series into an m x n matrix, where m is the dimension, and n the length.

toMatrix() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.realtime.SimpleMultiVariateTimeSeries

toMatrix(TimeSeries<?>) - Static method in class com.numericalmethod.suanshu.stats.timeseries.univariate.Util

Cast a time series into a column matrix, discarding the timestamps.

toString() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.Polynomial

toString() - Method in class com.numericalmethod.suanshu.analysis.function.rn2r1.RealScalarFunctionFixedVariables.Value

toString() - Method in class com.numericalmethod.suanshu.interval.Interval

toString() - Method in class com.numericalmethod.suanshu.interval.Intervals

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.CharacteristicPolynomial

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.ImmutableMatrix

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle.SymmetricMatrix

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.GivensMatrix

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.MatrixMathImpl

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseVector.Entry

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseVector

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.ElementaryOperation

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.Householder.Context

toString() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.SubMatrixRef

toString() - Method in class com.numericalmethod.suanshu.matrix.generic.matrixtype.ComplexMatrix

toString() - Method in class com.numericalmethod.suanshu.matrix.generic.matrixtype.GenericMatrix

toString() - Method in class com.numericalmethod.suanshu.matrix.generic.matrixtype.RealMatrix

toString() - Method in class com.numericalmethod.suanshu.number.complex.Complex

toString(double[][]) - Static method in class com.numericalmethod.suanshu.number.DoubleUtils

Convert a double[][] array to the format that we can copy and paste to re-create the array in Java code.

toString() - Method in class com.numericalmethod.suanshu.number.Real

toString() - Method in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau.Label

toString() - Method in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.Covariance

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.moment.Kurtosis

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.moment.Mean

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.moment.Moments

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.moment.Skewness

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.moment.Variance

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.rank.Max

toString() - Method in class com.numericalmethod.suanshu.stats.descriptive.rank.Min

toString() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.GenericTimeTimeSeries

toString() - Method in class com.numericalmethod.suanshu.stats.timeseries.multivariate.realtime.SimpleMultiVariateTimeSeries

toString() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.GenericTimeTimeSeries

toString() - Method in class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.SimpleTimeSeries

toString() - Method in class com.numericalmethod.suanshu.time.ComparableDateTime

toString() - Method in class com.numericalmethod.suanshu.vector.doubles.dense.DenseVector

toString() - Method in class com.numericalmethod.suanshu.vector.doubles.ImmutableVector

toVector(TimeSeries<?>) - Static method in class com.numericalmethod.suanshu.stats.timeseries.univariate.Util

Cast a time series into a vector, discarding the timestamps.

tr(Matrix) - Static method in class com.numericalmethod.suanshu.matrix.doubles.operation.Measure

Compute the sum of the diagonal elements, i.e., the trace of a matrix.

train(HiddenMarkovModel, int[]) - Method in class com.numericalmethod.suanshu.stats.hmm.HmmTrainByEM

Construct a trained (discrete) hidden Markov model using the train algorithm.

transpose(Matrix) - Method in interface com.numericalmethod.suanshu.matrix.doubles.matrixtype.mathoperation.MatrixMathOperation

t(A)

transpose(Matrix) - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.mathoperation.SimpleMatrixMathOperation

transposeSolve(Vector) - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner.IdentityPreconditioner

Returns the input Vector x.

transposeSolve(Vector) - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner.JacobiPreconditioner

P-t = P-1 for this preconditioner.

transposeSolve(Vector) - Method in interface com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner.Preconditioner

Solve Mtv = x, where M is the preconditioner matrix.

transposeSolve(Vector) - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner.SsorPreconditioner

M-tx = M-1x because M is symmetric.

Trapezoidal - Class in com.numericalmethod.suanshu.analysis.integration.univariate.riemann

The Trapezoidal rule is a closed type Newton–Cotes formula, where the integral interval is evenly divided into N sub-intervals.

Trapezoidal(double, int) - Constructor for class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Trapezoidal

Construct an integrator that uses the Trapezoidal rule.

trend - Variable in class com.numericalmethod.suanshu.stats.test.timeseries.adf.AdfAsymptoticDistribution

the type of augmented Dickey-Fuller (ADF) test

trend - Variable in class com.numericalmethod.suanshu.stats.test.timeseries.adf.AdfFiniteSampleDistribution

the type of augmented Dickey-Fuller (ADF) test

trend - Variable in class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.MADecomposition

the estimated trend of the time series

TriangularMatrix<T extends TriangularMatrix> - Class in com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.triangle

A triangular matrix is a square matrix where all entries below (or above) the main diagonal are zero.

tridiagonal(Matrix, double) - Static method in class com.numericalmethod.suanshu.matrix.doubles.IsMatrix

Check if a matrix is tridiagonal.

Tridiagonalization - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.diagonalization

A tridiagonal matrix A is a matrix such that it has non-zero elements only in the main diagonal, the first diagonal below this, and the first diagonal above the main diagonal.

Tridiagonalization(Matrix) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.diagonalization.Tridiagonalization

Construct an instance of the Tridiagonalization process.

TridiagonalMatrix - Class in com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal

This class represents a matrix with non-zero entries only on the super, main and sub diagonals.

TridiagonalMatrix(int) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.TridiagonalMatrix

Construct a tridiagonal matrix of dimension dim * dim.

TridiagonalMatrix(double[][]) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.TridiagonalMatrix

Construct a tridiagonal matrix from a 2D double[][] array.

TridiagonalMatrix(TridiagonalMatrix) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.TridiagonalMatrix

Copy constructor performing a deep copy.

truncation - Variable in class com.numericalmethod.suanshu.stats.test.timeseries.adf.AdfFiniteSampleDistribution

the number of truncated values

ts - Variable in class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Iterator

the time series to be iterated

TSS - Variable in class com.numericalmethod.suanshu.stats.regression.linear.ols.Residuals

diagnostic measure: the total sum of squares, Σ((y-y_mean)^2)

type - Variable in class com.numericalmethod.suanshu.analysis.differentiation.univariate.FiniteDifference

the type of finite difference chosen

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.Cubic

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.jenkinstraub.JenkinsTraubReal

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.Linear

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.Polyroot

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.Quadratic

type() - Method in class com.numericalmethod.suanshu.analysis.function.polynomial.root.Quartic

type() - Method in interface com.numericalmethod.suanshu.analysis.function.polynomial.root.Solver

Get the type of the solver.

type - Variable in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.EulerMaclaurin

indicate whether the two end points are included for computation

type - Variable in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.PowerLawSingularity

type() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.diagonal.BidiagonalMatrix

Get the type of the bidiagonal matrix.

type - Variable in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau.Label

type - Variable in class com.numericalmethod.suanshu.stats.descriptive.rank.Quantile

the quantile definition

type - Variable in class com.numericalmethod.suanshu.stats.test.distribution.kolmogorov.KolmogorovSmirnov

the type of Kolmogorov-Smirnov test to be performed

type - Variable in class com.numericalmethod.suanshu.stats.test.timeseries.adf.AugmentedDickeyFuller

the trend type