pal.math

Class NumericalDerivative

java.lang.Object

pal.math.NumericalDerivative

public class NumericalDerivative
extends Object

approximates numerically the first and second derivatives of a function of a single variable and approximates gradient and diagonal of Hessian for multivariate functions

Author:

Korbinian Strimmer

Constructor Summary

Constructors

Constructor and Description
NumericalDerivative()

Method Summary

Modifier and Type	Method and Description
static double[]	diagonalHessian(MultivariateFunction f, double[] x) determine diagonal of Hessian
static double	firstDerivative(UnivariateFunction f, double x) determine first derivative
static double[]	gradient(MultivariateFunction f, double[] x) determine gradient
static void	gradient(MultivariateFunction f, double[] x, double[] grad) determine gradient
static double	secondDerivative(UnivariateFunction f, double x) determine second derivative

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NumericalDerivative

public NumericalDerivative()

Method Detail

firstDerivative

public static double firstDerivative(UnivariateFunction f,
                                     double x)

determine first derivative

Parameters:

f - univariate function

x - argument

Returns:

first derivate at x

secondDerivative

public static double secondDerivative(UnivariateFunction f,
                                      double x)

determine second derivative

Parameters:

f - univariate function

x - argument

Returns:

second derivate at x

gradient

public static double[] gradient(MultivariateFunction f,
                                double[] x)

determine gradient

Parameters:

f - multivariate function

x - argument vector

Returns:

gradient at x

gradient

public static void gradient(MultivariateFunction f,
                            double[] x,
                            double[] grad)

determine gradient

Parameters:

f - multivariate function

x - argument vector

grad - vector for gradient

diagonalHessian

public static double[] diagonalHessian(MultivariateFunction f,
                                       double[] x)

determine diagonal of Hessian

Parameters:

f - multivariate function

x - argument vector

Returns:

vector with diagonal entries of Hessian