gov.sandia.cognition.statistics.distribution

Class LogisticDistribution.CDF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.AbstractDistribution<NumberType>

gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<java.lang.Double>

gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution

gov.sandia.cognition.statistics.distribution.LogisticDistribution

gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, ClosedFormDifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, Vectorizable, ScalarFunction<java.lang.Double>, UnivariateScalarFunction, ClosedFormComputableDistribution<java.lang.Double>, ClosedFormCumulativeDistributionFunction<java.lang.Double>, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, ComputableDistribution<java.lang.Double>, CumulativeDistributionFunction<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, InvertibleCumulativeDistributionFunction<java.lang.Double>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

LogisticDistribution

public static class LogisticDistribution.CDF
extends LogisticDistribution
implements SmoothCumulativeDistributionFunction, InvertibleCumulativeDistributionFunction<java.lang.Double>

CDF of the LogisticDistribution

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.LogisticDistribution

LogisticDistribution.CDF, LogisticDistribution.PDF

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.distribution.LogisticDistribution

DEFAULT_MEAN, DEFAULT_SCALE, mean, scale

Constructor Summary

Constructors

Constructor and Description
CDF() Default constructor
CDF(double mean, double scale) Creates a new instance of CDF
CDF(LogisticDistribution other) Copy constructor

Method Summary

Modifier and Type	Method and Description
java.lang.Double	differentiate(java.lang.Double input) Differentiates the output with respect to the input
double	evaluate(double input) Produces a double output for the given double input
java.lang.Double	evaluate(java.lang.Double input) Evaluates the function on the given input and returns the output.
double	evaluateAsDouble(java.lang.Double input) Evaluates the scalar function as a double.
LogisticDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.
LogisticDistribution.PDF	getDerivative() Gets the closed-form derivative of the function.
java.lang.Double	inverse(double probability) Computes the inverse of the CDF for the given probability.

Methods inherited from class gov.sandia.cognition.statistics.distribution.LogisticDistribution

clone, convertFromVector, convertToVector, getMaxSupport, getMeanAsDouble, getMinSupport, getProbabilityFunction, getScale, getVariance, sampleAsDouble, sampleInto, setMean, setScale

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution

getMean, sampleAsDoubles, sampleInto

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

sample, sample

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution

getMean, getProbabilityFunction, sampleAsDouble, sampleAsDoubles, sampleInto

Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution

getMaxSupport, getMeanAsDouble, getMinSupport, getVariance

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample, sampleInto

Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable

clone, convertFromVector, convertToVector

Constructor Detail

CDF

public CDF()

Default constructor

CDF

public CDF(double mean,
           double scale)

Creates a new instance of CDF

Parameters:

mean - Mean (median and mode) of the distribution.

scale - Scale of the distribution, proportionate to the standard deviation, must be greater than zero.

CDF

public CDF(LogisticDistribution other)

Copy constructor

Parameters:

other - LogisticDistribution to copy

Method Detail

getDerivative

public LogisticDistribution.PDF getDerivative()

Description copied from interface: ClosedFormDifferentiableEvaluator

Gets the closed-form derivative of the function.

Specified by:

getDerivative in interface ClosedFormDifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>

Specified by:

getDerivative in interface SmoothCumulativeDistributionFunction

Returns:

Closed-form derivative of the function.

evaluate

public java.lang.Double evaluate(java.lang.Double input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<java.lang.Double,java.lang.Double>

Specified by:

evaluate in interface ScalarFunction<java.lang.Double>

Specified by:

evaluate in interface UnivariateScalarFunction

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

evaluateAsDouble

public double evaluateAsDouble(java.lang.Double input)

Description copied from interface: ScalarFunction

Evaluates the scalar function as a double.

Specified by:

evaluateAsDouble in interface ScalarFunction<java.lang.Double>

Specified by:

evaluateAsDouble in interface UnivariateScalarFunction

Parameters:

input - The input value.

Returns:

The scalar output calculated from the given input.

evaluate

public double evaluate(double input)

Description copied from interface: UnivariateScalarFunction

Produces a double output for the given double input

Specified by:

evaluate in interface UnivariateScalarFunction

Parameters:

input - Input to the Evaluator

Returns:

output at the given input

differentiate

public java.lang.Double differentiate(java.lang.Double input)

Description copied from interface: DifferentiableEvaluator

Differentiates the output with respect to the input

Specified by:

differentiate in interface DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>

Parameters:

input - Input about which to compute the derivative

Returns:

Derivative of the output with respect to the given input

getCDF

public LogisticDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<java.lang.Double>

Specified by:

getCDF in interface SmoothUnivariateDistribution

Specified by:

getCDF in interface UnivariateDistribution<java.lang.Double>

Overrides:

getCDF in class LogisticDistribution

Returns:

CDF of the scalar distribution.

inverse

public java.lang.Double inverse(double probability)

Description copied from interface: InvertibleCumulativeDistributionFunction

Computes the inverse of the CDF for the given probability. That is, compute the value "x" such that p=CDF(x).

Specified by:

inverse in interface InvertibleCumulativeDistributionFunction<java.lang.Double>

Parameters:

probability - Probability to invert.

Returns:

Inverse of the CDF for the given probability.