Modifier and Type	Class and Description
public static class	Logistic.Parametric Parametric function where the input array contains the parameters of the `logistic function`, ordered as follows: k m b q a n

Modifier and Type

Class and Description

public static class

Logistic.Parametric

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

Field Summary

Modifier and Type	Field and Description
private final double	a Lower asymptote.
private final double	b Growth rate.
private final double	k Upper asymptote.
private final double	m Abscissa of maximum growth.
private final double	oneOverN Parameter that affects near which asymptote maximum growth occurs.
private final double	q Parameter that affects the position of the curve along the ordinate axis.

Modifier and Type

Field and Description

private final double

Lower asymptote.

private final double

Growth rate.

private final double

Upper asymptote.

private final double

Abscissa of maximum growth.

private final double

oneOverN

Parameter that affects near which asymptote maximum growth occurs.

private final double

Parameter that affects the position of the curve along the ordinate axis.

Constructor Summary

Access	Constructor and Description
public	Logistic(double If `b > 0`, value of the function for x going towards +∞. If `b < 0`, value of the function for x going towards -∞. k, double Abscissa of maximum growth. m, double Growth rate. b, double Parameter that affects the position of the curve along the ordinate axis. q, double If `b > 0`, value of the function for x going towards -∞. If `b < 0`, value of the function for x going towards +∞. a, double Parameter that affects near which asymptote the maximum growth occurs. n)

Access

Constructor and Description

public

Logistic(double

If b > 0, value of the function for x going towards +∞. If b < 0, value of the function for x going towards -∞.

k, double

Abscissa of maximum growth.

m, double

Growth rate.

b, double

Parameter that affects the position of the curve along the ordinate axis.

q, double

If b > 0, value of the function for x going towards -∞. If b < 0, value of the function for x going towards +∞.

a, double

Parameter that affects near which asymptote the maximum growth occurs.

Method Summary

Modifier and Type	Method and Description
public UnivariateFunction	derivative() Implements org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative. Deprecated as of 3.1, replaced by `value(DerivativeStructure)` Returns the derivative of the function
public double	value(double Point at which the function value should be computed. x) Implements org.apache.commons.math3.analysis.UnivariateFunction.value. Compute the value of the function.
private static double	Returns: the value of the function. value(double `m - x`. mMinusX, double `k`. k, double `b`. b, double `q`. q, double `a`. a, double `1 / n`. oneOverN)
public DerivativeStructure	value(final DerivativeStructure function input value t) Implements org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value. Simple mathematical function.

Modifier and Type

Method and Description

public UnivariateFunction

derivative()

Implements org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative.

Deprecated as of 3.1, replaced by value(DerivativeStructure)

Returns the derivative of the function

public double

value(double

Point at which the function value should be computed.

Implements org.apache.commons.math3.analysis.UnivariateFunction.value.

Compute the value of the function.

private static double

Returns:

the value of the function.

value(double

m - x.

mMinusX, double

k.

k, double

b.

b, double

q.

q, double

a.

a, double

1 / n.

oneOverN)

public DerivativeStructure

value(final DerivativeStructure

function input value

Implements org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value.

Simple mathematical function.

Field Detail

a	back to summary
private final double a Lower asymptote.

back to summary

private final double a

Lower asymptote.

b	back to summary
private final double b Growth rate.

back to summary

private final double b

Growth rate.

k	back to summary
private final double k Upper asymptote.

back to summary

private final double k

Upper asymptote.

m	back to summary
private final double m Abscissa of maximum growth.

back to summary

private final double m

Abscissa of maximum growth.

oneOverN	back to summary
private final double oneOverN Parameter that affects near which asymptote maximum growth occurs.

oneOverN

back to summary

private final double oneOverN

Parameter that affects near which asymptote maximum growth occurs.

q	back to summary
private final double q Parameter that affects the position of the curve along the ordinate axis.

back to summary

private final double q

Parameter that affects the position of the curve along the ordinate axis.

Constructor Detail

Logistic	back to summary
public Logistic(double k, double m, double b, double q, double a, double n) throws NotStrictlyPositiveException Parameters k:double If `b > 0`, value of the function for x going towards +∞. If `b < 0`, value of the function for x going towards -∞. m:double Abscissa of maximum growth. b:double Growth rate. q:double Parameter that affects the position of the curve along the ordinate axis. a:double If `b > 0`, value of the function for x going towards -∞. If `b < 0`, value of the function for x going towards +∞. n:double Parameter that affects near which asymptote the maximum growth occurs. Exceptions NotStrictlyPositiveException: if `n <= 0`.

Logistic

back to summary

public Logistic(double k, double m, double b, double q, double a, double n) throws NotStrictlyPositiveException

Parameters

k:double: If b > 0, value of the function for x going towards +∞. If b < 0, value of the function for x going towards -∞.
m:double: Abscissa of maximum growth.
b:double: Growth rate.
q:double: Parameter that affects the position of the curve along the ordinate axis.
a:double: If b > 0, value of the function for x going towards -∞. If b < 0, value of the function for x going towards +∞.
n:double: Parameter that affects near which asymptote the maximum growth occurs.

Exceptions

NotStrictlyPositiveException:: if n <= 0.

Method Detail

derivative back to summary

derivative	back to summary
public UnivariateFunction derivative() Implements org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative. Doc from org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative. Deprecated as of 3.1, replaced by `value(DerivativeStructure)` Returns the derivative of the function Returns:UnivariateFunction the derivative function Annotations @Deprecated

public UnivariateFunction derivative()

Implements org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative.

Doc from org.apache.commons.math3.analysis.DifferentiableUnivariateFunction.derivative.

Deprecated

as of 3.1, replaced by value(DerivativeStructure)

Returns the derivative of the function

Returns:UnivariateFunction

the derivative function

Annotations

@Deprecated

value	back to summary
public double value(double x) Implements org.apache.commons.math3.analysis.UnivariateFunction.value. Doc from org.apache.commons.math3.analysis.UnivariateFunction.value. Compute the value of the function. Parameters x:double Point at which the function value should be computed. Returns:double the value of the function.

value

back to summary

public double value(double x)

Implements org.apache.commons.math3.analysis.UnivariateFunction.value.

Doc from org.apache.commons.math3.analysis.UnivariateFunction.value.

Compute the value of the function.

Parameters

x:double: Point at which the function value should be computed.

Returns:double

the value of the function.

value	back to summary
private static double value(double mMinusX, double k, double b, double q, double a, double oneOverN) Parameters mMinusX:double `m - x`. k:double `k`. b:double `b`. q:double `q`. a:double `a`. oneOverN:double `1 / n`. Returns:double the value of the function.

value back to summary

value	back to summary
public DerivativeStructure value(final DerivativeStructure t) Implements org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value. Doc from org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value. Simple mathematical function. `UnivariateDifferentiableFunction` classes compute both the value and the first derivative of the function. Parameters t:DerivativeStructure function input value Returns:DerivativeStructure function result Since 3.1

public DerivativeStructure value(final DerivativeStructure t)

Implements org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value.

Doc from org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction.value.

Simple mathematical function.

UnivariateDifferentiableFunction classes compute both the value and the first derivative of the function.

Parameters

t:DerivativeStructure: function input value

Returns:DerivativeStructure

function result

Since

3.1

org.apache.commons.math3.analysis.function back to summary

public Class Logistic.Parametric

Class Inheritance

extends Object
implements ParametricUnivariateFunction

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

All Implemented Interfaces

org.apache.commons.math3.analysis.ParametricUnivariateFunction

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

Constructor Summary

Access	Constructor and Description
public	Parametric()

Method Summary

Modifier and Type	Method and Description
public double[]	Returns: the gradient vector at `x`. gradient(double Value at which the gradient must be computed. x, double... Values for `k`, `m`, `b`, `q`, `a` and `n`. param) Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.gradient. Computes the value of the gradient at `x`.
private void	validateParameters(double[] Values for `k`, `m`, `b`, `q`, `a` and `n`. param) Validates parameters to ensure they are appropriate for the evaluation of the `value(double, double[])` and `gradient(double, double[])` methods.
public double	Returns: the value of the function. value(double Value for which the function must be computed. x, double... Values for `k`, `m`, `b`, `q`, `a` and `n`. param) Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.value. Computes the value of the sigmoid at `x`.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

Constructor Detail

Parametric	back to summary
public Parametric()

Method Detail

gradient back to summary

gradient	back to summary
public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.gradient. 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. Parameters x:double Value at which the gradient must be computed. param:double[] Values for `k`, `m`, `b`, `q`, `a` and `n`. Returns:double[] the gradient vector at `x`. Exceptions NullArgumentException: if `param` is `null`. DimensionMismatchException: if the size of `param` is not 6. NotStrictlyPositiveException: if `param[5] <= 0`.

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

Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.gradient.

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.

Parameters

x:double: Value at which the gradient must be computed.
param:double[]: Values for k, m, b, q, a and n.

Returns:double[]

the gradient vector at x.

Exceptions

NullArgumentException:: if param is null.
DimensionMismatchException:: if the size of param is not 6.
NotStrictlyPositiveException:: if param[5] <= 0.

validateParameters back to summary

validateParameters	back to summary
private void validateParameters(double[] param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Validates parameters to ensure they are appropriate for the evaluation of the `value(double, double[])` and `gradient(double, double[])` methods. Parameters param:double[] Values for `k`, `m`, `b`, `q`, `a` and `n`. Exceptions NullArgumentException: if `param` is `null`. DimensionMismatchException: if the size of `param` is not 6. NotStrictlyPositiveException: if `param[5] <= 0`.

private void validateParameters(double[] param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException

Validates parameters to ensure they are appropriate for the evaluation of the value(double, double[]) and gradient(double, double[]) methods.

Parameters

param:double[]: Values for k, m, b, q, a and n.

Exceptions

NullArgumentException:: if param is null.
DimensionMismatchException:: if the size of param is not 6.
NotStrictlyPositiveException:: if param[5] <= 0.

value back to summary

value	back to summary
public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.value. Computes the value of the sigmoid at `x`. Parameters x:double Value for which the function must be computed. param:double[] Values for `k`, `m`, `b`, `q`, `a` and `n`. Returns:double the value of the function. Exceptions NullArgumentException: if `param` is `null`. DimensionMismatchException: if the size of `param` is not 6. NotStrictlyPositiveException: if `param[5] <= 0`.

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

Implements org.apache.commons.math3.analysis.ParametricUnivariateFunction.value.

Computes the value of the sigmoid at x.

Parameters

x:double: Value for which the function must be computed.
param:double[]: Values for k, m, b, q, a and n.

Returns:double

the value of the function.

Exceptions

NullArgumentException:: if param is null.
DimensionMismatchException:: if the size of param is not 6.
NotStrictlyPositiveException:: if param[5] <= 0.

public Class Logistic

Nested and Inner Type Summary

Field Summary

Constructor Summary

Method Summary

Field Detail

Constructor Detail

Method Detail

public Class Logistic.Parametric

Constructor Summary

Method Summary

Constructor Detail

Method Detail