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 class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.EulerMaclaurin

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.Simpson

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

Get a copy of the H matrix.

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

Get a copy of the Householder matrix H.

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

the Hessian function, H(x)

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

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

Hadi - Variable in class com.numericalmethod.suanshu.stats.regression.linear.ols.Diagnostics

Hadi's influence measure

Halley - Class in com.numericalmethod.suanshu.analysis.uniroot

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

Halley(UnivariateRealFunction, UnivariateRealFunction, UnivariateRealFunction, double) - Constructor for class com.numericalmethod.suanshu.analysis.uniroot.Halley

Construct an instance of Halley's root finding algorithm.

Halley(UnivariateRealFunction, double) - Constructor for class com.numericalmethod.suanshu.analysis.uniroot.Halley

Construct an instance of Halley's root finding algorithm.

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

The Harvey-Godfrey test is used to test for heteroskedasticity in a linear regression model.

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.

hasApproximately(double, Number...) - Method in class com.numericalmethod.suanshu.datastructure.list.NumberList

Check whether the list contains the numbers.

hasApproximately(double, String...) - Method in class com.numericalmethod.suanshu.datastructure.list.NumberList

Check whether the list contains the numbers.

hasExactly(Number...) - Method in class com.numericalmethod.suanshu.datastructure.list.NumberList

Check whether the list contains the numbers.

hasExactly(String...) - Method in class com.numericalmethod.suanshu.datastructure.list.NumberList

Check whether the list contains the numbers.

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

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.dense.DenseData

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

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

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.SparseElement

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

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

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.multivariate.GenericTimeTimeSeries

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

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

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

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

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

hasNext() - Method in class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Iterator

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

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

Get the set of the names of the columns.

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

This class implements the operations for an upper Hessenberg matrix.

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

Create a Hessenberg utility class with the default deflation criterion.

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

Create a Hessenberg utility class with a customized deflation criterion.

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

Users can override the default implementation to define their 0 threshold.

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

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

This class encapsulates the indices for the upper left hand corner, and lower right hand corner of H22.

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

User implements this class to decide whether to split an upper Hessenberg into multiple smaller upper Hessenberg when the sub-diagonal entries are sufficiently small.

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

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.HessenbergDecomposition

Construct an instance of 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, double...) - Constructor for class com.numericalmethod.suanshu.analysis.differentiation.multivariate.Hessian

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

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

Compute the Hessian function, H(x), for a real scalar function f(x).

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

Construct a HessianFunction to compute the Hessian matrix numerically.

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

projection matrix H-hat

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

This class represents a hidden Markov model as defined by Rabiner.

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

Construct a (discrete) hidden Markov model.

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

Construct a (discrete) hidden Markov model with equal initial state probabilities

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 of dimension dim * dim.

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

This interface represents a Hilbert space.

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

the Hessian evaluated at xk

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

This class simulates a (discrete) hidden Markov model as defined by Rabiner (1989).

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

Construct a simulator for a (discrete) hidden Markov model.

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

This class trains a HMM model by observations using the train algorithm.

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

homogeneousSoln() - Method in class com.numericalmethod.suanshu.matrix.doubles.linearsystem.Solver

Get the basis of the homogeneous solution for the linear system, Ax = b.

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

Hong Kong

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.

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

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

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

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

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

Context information about a Householder transformation.

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

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

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

Construct an instance of the Householder reflection process to orthogonalize a matrix.

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

Construct an instance of the Householder reflection process to orthogonalize a matrix.

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

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

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

Construct an instance of Huang to minimize an objective function.

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 samples.