gov.sandia.cognition.statistics.distribution

Class ScalarMixtureDensityModel.CDF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.statistics.distribution.LinearMixtureModel<java.lang.Double,SmoothUnivariateDistribution>

gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel

gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.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>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

ScalarMixtureDensityModel

public static class ScalarMixtureDensityModel.CDF
extends ScalarMixtureDensityModel
implements SmoothCumulativeDistributionFunction

CDFof the SMDM

See Also:

Serialized Form

Nested Class Summary

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

ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.EMLearner, ScalarMixtureDensityModel.PDF

Field Summary

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

distributions, priorWeights

Constructor Summary

Constructors

Constructor and Description
CDF() Creates a new instance of ScalarMixtureDensityModel
CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions) Creates a new instance of ScalarMixtureDensityModel
CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions, double[] priorWeights) Creates a new instance of ScalarMixtureDensityModel
CDF(ScalarMixtureDensityModel other) Copy constructor
CDF(SmoothUnivariateDistribution... distributions) Creates a new instance of ScalarMixtureDensityModel

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.
ScalarMixtureDensityModel.CDF	getCDF() Gets the CDF of a scalar distribution.
ScalarMixtureDensityModel.PDF	getDerivative() Gets the closed-form derivative of the function.

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

clone, convertFromVector, convertToVector, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getProbabilityFunction, getVariance, sampleAsDouble, sampleAsDoubles, sampleInto

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

getDistributionCount, getDistributions, getPriorWeights, getPriorWeightSum, sample, sampleInto, setDistributions, setPriorWeights, toString

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

sample

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, 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()

Creates a new instance of ScalarMixtureDensityModel

CDF

public CDF(SmoothUnivariateDistribution... distributions)

Creates a new instance of ScalarMixtureDensityModel

Parameters:

distributions - Distributions that comprise the SMDM with equal prior weight

CDF

public CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions)

Creates a new instance of ScalarMixtureDensityModel

Parameters:

distributions - Distributions that comprise the SMDM with equal prior weight

CDF

public CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions,
           double[] priorWeights)

Creates a new instance of ScalarMixtureDensityModel

Parameters:

distributions - Distributions that comprise the SMDM

priorWeights - Weights proportionate by which the distributions are sampled

CDF

public CDF(ScalarMixtureDensityModel other)

Copy constructor

Parameters:

other - SMDM to copy

Method Detail

getDerivative

public ScalarMixtureDensityModel.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 ScalarMixtureDensityModel.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 ScalarMixtureDensityModel

Returns:

CDF of the scalar distribution.