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

java.lang.Object
  extended by org.apache.commons.math3.analysis.function.Sigmoid.Parametric
All Implemented Interfaces:
ParametricUnivariateFunction
Enclosing class:
Sigmoid

public static class Sigmoid.Parametric
extends Object
implements ParametricUnivariateFunction

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


Constructor Summary
Sigmoid.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

Sigmoid.Parametric

public Sigmoid.Parametric()
Method Detail

value

public double value(double x,
                    double... param)
             throws NullArgumentException,
                    DimensionMismatchException
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 of lower asymptote and higher asymptote.
Returns:
the value of the function.
Throws:
NullArgumentException - if param is null.
DimensionMismatchException - if the size of param is not 2.

gradient

public double[] gradient(double x,
                         double... param)
                  throws NullArgumentException,
                         DimensionMismatchException
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 (lower asymptote and higher asymptote).

Specified by:
gradient in interface ParametricUnivariateFunction
Parameters:
x - Value at which the gradient must be computed.
param - Values for lower asymptote and higher asymptote.
Returns:
the gradient vector at x.
Throws:
NullArgumentException - if param is null.
DimensionMismatchException - if the size of param is not 2.


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