gov.sandia.cognition.statistics.distribution

Class UnivariateGaussian.PDF

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.UnivariateGaussian

gov.sandia.cognition.statistics.distribution.UnivariateGaussian.PDF

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, Vectorizable, ScalarFunction<java.lang.Double>, UnivariateScalarFunction, ClosedFormComputableDistribution<java.lang.Double>, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, ComputableDistribution<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, EstimableDistribution<java.lang.Double,UnivariateGaussian>, ProbabilityDensityFunction<java.lang.Double>, ProbabilityFunction<java.lang.Double>, SmoothUnivariateDistribution, UnivariateDistribution<java.lang.Double>, UnivariateProbabilityDensityFunction, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

UnivariateGaussian

public static class UnivariateGaussian.PDF
extends UnivariateGaussian
implements UnivariateProbabilityDensityFunction

PDF of the underlying Gaussian.

See Also:

Serialized Form

Nested Class Summary

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

UnivariateGaussian.CDF, UnivariateGaussian.ErrorFunction, UnivariateGaussian.IncrementalEstimator, UnivariateGaussian.MaximumLikelihoodEstimator, UnivariateGaussian.PDF, UnivariateGaussian.SufficientStatistic, UnivariateGaussian.WeightedMaximumLikelihoodEstimator

Field Summary

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

BIG_Z, DEFAULT_MEAN, DEFAULT_VARIANCE, mean, PI2, SQRT2, variance

Constructor Summary

Constructors

Constructor and Description
PDF() Creates a new instance of UnivariateGaussian with zero mean and unit variance
PDF(double mean, double variance) Creates a new instance of UnivariateGaussian
PDF(UnivariateGaussian other) Copy constructor

Method Summary

Modifier and Type	Method and Description
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.
static double	evaluate(double input, double mean, double variance) Computes the value of the Probability Density Function at the input
double	evaluateAsDouble(java.lang.Double input) Evaluates the scalar function as a double.
UnivariateGaussian.PDF	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
double	logEvaluate(double input) Evaluate the natural logarithm of the distribution function.
double	logEvaluate(java.lang.Double input) Evaluate the natural logarithm of the distribution function.
static double	logEvaluate(double input, double mean, double variance) Computes the natural logarithm of the pdf.

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

clone, convertFromVector, convertToVector, convolve, getCDF, getEstimator, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getStandardDeviation, getVariance, sampleAsDouble, sampleInto, setMean, setVariance, times, toString

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

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, wait, wait, wait

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

getCDF, getMean, 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

PDF

public PDF()

Creates a new instance of UnivariateGaussian with zero mean and unit variance

PDF

public PDF(double mean,
           double variance)

Creates a new instance of UnivariateGaussian

Parameters:

mean - First central moment (expectation) of the distribution

variance - Second central moment (square of standard deviation) of the distribution

PDF

public PDF(UnivariateGaussian other)

Copy constructor

Parameters:

other - UnivariateGaussian to copy

Method Detail

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

evaluate

public static double evaluate(double input,
                              double mean,
                              double variance)

Computes the value of the Probability Density Function at the input

Parameters:

input - Input value to compute the PDF at, that is, p(input|mean,variance)

mean - Mean of the distribution

variance - Variance of the distribution

Returns:

Value of the PDF at the input, p(input|mean,variance)

logEvaluate

public double logEvaluate(java.lang.Double input)

Description copied from interface: ProbabilityFunction

Evaluate the natural logarithm of the distribution function. This is sometimes more efficient than evaluating the distribution function itself, and when evaluating the product of many independent or exchangeable samples.

Specified by:

logEvaluate in interface ProbabilityFunction<java.lang.Double>

Parameters:

input - The input to be evaluated

Returns:

Natural logarithm of the distribution function.

logEvaluate

public double logEvaluate(double input)

Description copied from interface: UnivariateProbabilityDensityFunction

Evaluate the natural logarithm of the distribution function. This is sometimes more efficient than evaluating the distribution function itself, and when evaluating the product of many independent or exchangeable samples.

Specified by:

logEvaluate in interface UnivariateProbabilityDensityFunction

Parameters:

input - The input value.

Returns:

The natural logarithm of the distribution function.

logEvaluate

public static double logEvaluate(double input,
                                 double mean,
                                 double variance)

Computes the natural logarithm of the pdf.

Parameters:

input - Input to consider.

mean - Mean of the Gaussian.

variance - Variance of the Gaussian.

Returns:

Natural logarithm of the pdf.

getProbabilityFunction

public UnivariateGaussian.PDF getProbabilityFunction()

Description copied from interface: ComputableDistribution

Gets the distribution function associated with this Distribution, either the PDF or PMF.

Specified by:

getProbabilityFunction in interface ComputableDistribution<java.lang.Double>

Specified by:

getProbabilityFunction in interface ProbabilityDensityFunction<java.lang.Double>

Specified by:

getProbabilityFunction in interface SmoothUnivariateDistribution

Specified by:

getProbabilityFunction in interface UnivariateProbabilityDensityFunction

Overrides:

getProbabilityFunction in class UnivariateGaussian

Returns:

Distribution function associated with this Distribution.