org.apache.commons.math3.analysis.function
Class Logistic.Parametric

java.lang.Object
  org.apache.commons.math3.analysis.function.Logistic.Parametric

All Implemented Interfaces:

ParametricUnivariateFunction

Enclosing class:

Logistic

public static class Logistic.Parametric
extends Object
implements ParametricUnivariateFunction

Parametric function where the input array contains the parameters of the logit function, ordered as follows:

• Lower asymptote
• Higher asymptote

Constructor Summary

Logistic.Parametric()

Method Summary

double[]	gradient(double x, double... param) Computes the value of the gradient at x.
double	value(double x, double... param) Computes the value of the sigmoid at x.

Methods inherited from class java.lang.Object

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

Constructor Detail

Logistic.Parametric

public Logistic.Parametric()

Method Detail

value

public double value(double x,
                    double... param)
             throws NullArgumentException,
                    DimensionMismatchException,
                    NotStrictlyPositiveException

Computes the value of the sigmoid at x.

Specified by:

value in interface ParametricUnivariateFunction

Parameters:

x - Value for which the function must be computed.

param - Values for k, m, b, q, a and n.

Returns:

the value of the function.

Throws:

NullArgumentException - if param is null.

DimensionMismatchException - if the size of param is not 6.

NotStrictlyPositiveException - if param[5] <= 0.

gradient

public double[] gradient(double x,
                         double... param)
                  throws NullArgumentException,
                         DimensionMismatchException,
                         NotStrictlyPositiveException

Computes the value of the gradient at x. The components of the gradient vector are the partial derivatives of the function with respect to each of the parameters.

Specified by:

gradient in interface ParametricUnivariateFunction

Parameters:

x - Value at which the gradient must be computed.

param - Values for k, m, b, q, a and n.

Returns:

the gradient vector at x.

Throws:

NullArgumentException - if param is null.

DimensionMismatchException - if the size of param is not 6.

NotStrictlyPositiveException - if param[5] <= 0.