Class Logistic.Parametric
- java.lang.Object
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- org.apache.commons.math4.legacy.analysis.function.Logistic.Parametric
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- 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 thelogistic function. Ordered as follows:- k
- m
- b
- q
- a
- n
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Constructor Summary
Constructors Constructor Description Parametric()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double[]gradient(double x, double... param)Computes the value of the gradient atx.doublevalue(double x, double... param)Computes the value of the sigmoid atx.
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Constructor Detail
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Parametric
public Parametric()
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Method Detail
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value
public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
Computes the value of the sigmoid atx.- Specified by:
valuein interfaceParametricUnivariateFunction- Parameters:
x- Value for which the function must be computed.param- Values fork,m,b,q,aandn.- Returns:
- the value of the function.
- Throws:
NullArgumentException- ifparamisnull.DimensionMismatchException- if the size ofparamis not 6.NotStrictlyPositiveException- ifparam[5] <= 0.
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gradient
public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
Computes the value of the gradient atx. The components of the gradient vector are the partial derivatives of the function with respect to each of the parameters.- Specified by:
gradientin interfaceParametricUnivariateFunction- Parameters:
x- Value at which the gradient must be computed.param- Values fork,m,b,q,aandn.- Returns:
- the gradient vector at
x. - Throws:
NullArgumentException- ifparamisnull.DimensionMismatchException- if the size ofparamis not 6.NotStrictlyPositiveException- ifparam[5] <= 0.
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