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

H

H() - Method in interface com.numericalmethod.suanshu.analysis.differentiation.differentiability.C2

Get the Hessian matrix function, H, of a real valued function f.

h() - Method in interface com.numericalmethod.suanshu.analysis.integration.univariate.riemann.IterativeIntegrator

Get the discretization size for the current iteration.

h() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.newtoncotes.NewtonCotes

h() - Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.newtoncotes.Simpson

H() - Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.HessenbergDecomposition

Get the H matrix.

H() - Method in class com.numericalmethod.suanshu.matrix.doubles.operation.HouseholderReflection

Get the Householder matrix H = I - 2 * v * v'.

H() - Method in class com.numericalmethod.suanshu.optimization.problem.C2OptimProblemImpl

H(int) - Method in class com.numericalmethod.suanshu.stats.dlm.multivariate.MultivariateStateEquation

Get H(t), the covariance matrix of u_t.

H(int) - Method in class com.numericalmethod.suanshu.stats.dlm.univariate.StateEquation

Get H(t), the variance of u_t.

Hadi() - Method in class com.numericalmethod.suanshu.stats.regression.linear.ols.OLSDiagnostics

Hadi's influence measure.

HalleyRoot - Class in com.numericalmethod.suanshu.analysis.root

Halley's method is an iterative root finding method for a univariate function with a continuous second derivative, i.e., a C² function.

HalleyRoot(double, int) - Constructor for class com.numericalmethod.suanshu.analysis.root.HalleyRoot

Construct an instance of Halley's root finding algorithm.

HarveyGodfrey - Class in com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity

The Harvey-Godfrey test tests for conditional heteroskedasticity.

HarveyGodfrey(Residuals) - Constructor for class com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity.HarveyGodfrey

Perform the Harvey-Godfrey test to test for heteroskedasticity in a linear regression model.

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

Check if a double array contains any duplicates.

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

hashCode() - Method in class com.numericalmethod.suanshu.analysis.function.tuple.Pair

hashCode() - Method in class com.numericalmethod.suanshu.datastructure.FlexibleTable

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

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

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

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.DefaultMatrixStorage

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseData

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

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

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

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

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

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.Coordinates

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.CSRSparseMatrix

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.DOKSparseMatrix

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.LILSparseMatrix

hashCode() - Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseEntry

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

hashCode() - Method in class com.numericalmethod.suanshu.matrix.generic.matrixtype.GenericFieldMatrix

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

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

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

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.DateTimeGenericTimeSeries.Entry

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.multivariate.MultivariateGenericTimeTimeSeries

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.multivariate.MultivariateTimeSeries.Entry

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.multivariate.realtime.inttime.MultivariateSimpleTimeSeries

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

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.univariate.realtime.inttime.SimpleTimeSeries

hashCode() - Method in class com.numericalmethod.suanshu.stats.timeseries.datastructure.univariate.UnivariateTimeSeries.Entry

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

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

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

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

Check if a double array has any 0.

hav(double) - Static method in class com.numericalmethod.suanshu.geometry.TrigMath

Returns the haversed sine or haversine of an angle.

HeatEquationProblem1D - Class in com.numericalmethod.suanshu.analysis.differentialequation.pde.finitedifference.parabolic1d

A one-dimensional parabolic PDE problem called heat equation (or diffusion equation) of the following form.

HeatEquationProblem1D(double, double, double, UnivariateRealFunction, double, UnivariateRealFunction, double, UnivariateRealFunction) - Constructor for class com.numericalmethod.suanshu.analysis.differentialequation.pde.finitedifference.parabolic1d.HeatEquationProblem1D

Create a heat equation problem.

HeatEquationProblem2D - Class in com.numericalmethod.suanshu.analysis.differentialequation.pde.finitedifference.parabolic2d

A two-dimensional parabolic PDE problem called heat equation (or diffusion equation) of the following form.

HeatEquationProblem2D(double, double, double, double, BivariateRealFunction, TrivariateRealFunction) - Constructor for class com.numericalmethod.suanshu.analysis.differentialequation.pde.finitedifference.parabolic2d.HeatEquationProblem2D

Create a two-dimensional heat equation problem.

HermitePolynomials - Class in com.numericalmethod.suanshu.analysis.integration.univariate.riemann.gaussian.rule

A Hermite polynomial is defined by the recurrence relation below.

HermitePolynomials() - Constructor for class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.gaussian.rule.HermitePolynomials

HermiteRule - Class in com.numericalmethod.suanshu.analysis.integration.univariate.riemann.gaussian.rule

HermiteRule(int) - Constructor for class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.gaussian.rule.HermiteRule

Create a Hermite rule of the given order.

Hessenberg - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr

An upper Hessenberg matrix is a square matrix which has zero entries below the first sub-diagonal.

Hessenberg(Hessenberg.DeflationCriterion) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.Hessenberg

Construct a Hessenberg utility class.

Hessenberg() - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.Hessenberg

Construct a Hessenberg utility class with the default deflation criterion.

Hessenberg.DefaultDeflationCriterion - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr

The default deflation criterion is to use eq.

Hessenberg.DefaultDeflationCriterion(double) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.Hessenberg.DefaultDeflationCriterion

Construct the default deflation criterion.

Hessenberg.DefaultDeflationCriterion() - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.Hessenberg.DefaultDeflationCriterion

Construct the default deflation criterion.

Hessenberg.Deflation - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr

This class encapsulates the indices for the upper left hand corner and lower right hand corner of H₂₂ as a result of the deflation procedure.

Hessenberg.DeflationCriterion - Interface in com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr

Deflation of an upper Hessenberg matrix splits it into multiple smaller upper Hessenberg matrices when the sub-diagonal entries are sufficiently small.

HessenbergDecomposition - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr

Given a square matrix A, we find Q such that Q' * A * Q = H where H is a Hessenberg matrix.

HessenbergDecomposition(Matrix) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.qr.HessenbergDecomposition

Run the Hessenberg decomposition for a square matrix.

Hessian - Class in com.numericalmethod.suanshu.analysis.differentiation.multivariate

The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function.

Hessian(RealScalarFunction, Vector) - Constructor for class com.numericalmethod.suanshu.analysis.differentiation.multivariate.Hessian

Construct the Hessian matrix for a multivariate function f at point x.

Hessian() - Method in class com.numericalmethod.suanshu.analysis.function.rn2r1.QuadraticFunction

HessianFunction - Class in com.numericalmethod.suanshu.analysis.differentiation.multivariate

The Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x.

HessianFunction(RealScalarFunction) - Constructor for class com.numericalmethod.suanshu.analysis.differentiation.multivariate.HessianFunction

Construct the Hessian function of a real scalar function f.

Heteroskedasticity - Class in com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity

A heteroskedasticity test tests, for a linear regression model, whether the estimated variance of the residuals from a regression is dependent on the values of the independent variables (regressors).

Heteroskedasticity(Residuals) - Constructor for class com.numericalmethod.suanshu.stats.test.regression.linear.heteroskedasticity.Heteroskedasticity

Construct a heteroskedasticity test.

hHat() - Method in class com.numericalmethod.suanshu.stats.regression.linear.ols.OLSResiduals

Get the projection matrix, H-hat.

HiddenMarkovModel - Class in com.numericalmethod.suanshu.stats.hmm

In a (discrete) hidden Markov model, the state is not directly visible, but output, dependent on the state, is visible.

HiddenMarkovModel(Vector, Matrix, RandomNumberGenerator[]) - Constructor for class com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

Construct a hidden Markov model.

HiddenMarkovModel(HiddenMarkovModel) - Constructor for class com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

Copy constructor.

HilbertMatrix - Class in com.numericalmethod.suanshu.matrix.doubles.matrixtype

A Hilbert matrix, H, is a symmetric matrix with entries being the unit fractions H[i][j] = 1 / (i + j -1)

HilbertMatrix(int) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.matrixtype.HilbertMatrix

Construct a Hilbert matrix.

HilbertSpace<H,F extends Field<F> & java.lang.Comparable<F>> - Interface in com.numericalmethod.suanshu.mathstructure

A Hilbert space is an inner product space, an abstract vector space in which distances and angles can be measured.

HmmInnovation - Class in com.numericalmethod.suanshu.stats.hmm

An HMM innovation consists of a state and an observation in the state.

HmmInnovation(int, double) - Constructor for class com.numericalmethod.suanshu.stats.hmm.HmmInnovation

Construct an HMM innovation.

HomogeneousPathFollowing - Class in com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing

This implementation solves a Semi-Definite Programming problem using the Homogeneous Self-Dual Path-Following algorithm.

HomogeneousPathFollowing(double, double, double) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing.HomogeneousPathFollowing

Construct a Homogeneous Self-Dual Path-Following minimizer to solve semi-definite programming problems.

HomogeneousPathFollowing(double) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing.HomogeneousPathFollowing

Construct a Homogeneous Self-Dual Path-Following minimizer to solve semi-definite programming problems.

HomogeneousPathFollowing.Solution - Class in com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing

This is the solution to a Semi-Definite Programming problem using the Homogeneous Self-Dual Path-Following algorithm.

HomogeneousPathFollowing.Solution(PrimalDualPathFollowing, SDPDualProblem, double, double) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing.HomogeneousPathFollowing.Solution

solve the semi-definite programming problem using the Homogeneous Self-Dual Path-Following algorithm

HornerScheme - Class in com.numericalmethod.suanshu.analysis.function.polynomial

Horner scheme is an algorithm for the efficient evaluation of polynomials in monomial form.

HornerScheme(Polynomial, double) - Constructor for class com.numericalmethod.suanshu.analysis.function.polynomial.HornerScheme

Evaluate a polynomial at x.

Householder4SubVector - Class in com.numericalmethod.suanshu.matrix.doubles.operation

Faster implementation of Householder reflection for sub-vectors at a given index.

Householder4SubVector(int, Vector) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.Householder4SubVector

Householder4SubVector(int, int, Vector) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.Householder4SubVector

Householder4ZeroGenerator - Class in com.numericalmethod.suanshu.matrix.doubles.operation

Faster implementation of Householder reflection for zero generator.

Householder4ZeroGenerator(int) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.Householder4ZeroGenerator

HouseholderQR - Class in com.numericalmethod.suanshu.matrix.doubles.factorization.qr

Successive Householder reflections gradually transform a matrix A to the upper triangular form.

HouseholderQR(Matrix, double) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.qr.HouseholderQR

Run the Householder reflection process to orthogonalize a matrix.

HouseholderQR(Matrix) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.factorization.qr.HouseholderQR

Run the Householder reflection process to orthogonalize a matrix.

HouseholderReflection - Class in com.numericalmethod.suanshu.matrix.doubles.operation

A Householder transformation in the 3-dimensional space is the reflection of a vector in the plane.

HouseholderReflection(Vector) - Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.HouseholderReflection

Construct a Householder matrix from the vector that defines the hyperplane orthogonal to the vector.

HouseholderReflection.Context - Class in com.numericalmethod.suanshu.matrix.doubles.operation

This is the context information about a Householder transformation.

Hp - Class in com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing

This is the symmetrization operator as defined in eq.

Hp(Matrix) - Constructor for class com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing.Hp

Construct a symmetrization operator.

Hp() - Constructor for class com.numericalmethod.suanshu.optimization.constrained.convex.sdp.pathfollowing.Hp

Construct the symmetrization operator using an identity matrix.

HuangMinimizer - Class in com.numericalmethod.suanshu.optimization.unconstrained.quasinewton

Huang's updating formula is a family of formulas which encompasses the rank-one, DFP, BFGS as well as some other formulas.

HuangMinimizer(double, double, double, double, double, int) - Constructor for class com.numericalmethod.suanshu.optimization.unconstrained.quasinewton.HuangMinimizer

Construct a multivariate minimizer using Huang's method.

HuangMinimizer.HuangImpl - Class in com.numericalmethod.suanshu.optimization.unconstrained.quasinewton

an implementation of Huang's formula.

HuangMinimizer.HuangImpl(C2OptimProblem) - Constructor for class com.numericalmethod.suanshu.optimization.unconstrained.quasinewton.HuangMinimizer.HuangImpl

HypothesisTest - Class in com.numericalmethod.suanshu.stats.test

A statistical hypothesis test is a method of making decisions using experimental data.

HypothesisTest(double[]...) - Constructor for class com.numericalmethod.suanshu.stats.test.HypothesisTest

Construct an instance of HypothesisTest from the samples.