Package smile.stat.distribution

Class DiscreteExponentialFamilyMixture

java.lang.Object

smile.stat.distribution.AbstractDistribution

smile.stat.distribution.DiscreteDistribution

smile.stat.distribution.DiscreteMixture

smile.stat.distribution.DiscreteExponentialFamilyMixture

All Implemented Interfaces:

Serializable, Distribution

public class DiscreteExponentialFamilyMixture
extends DiscreteMixture

The finite mixture of distributions from discrete exponential family. The EM algorithm is provided to learn the mixture model from data.

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class smile.stat.distribution.DiscreteMixture

DiscreteMixture.Component

Field Summary

Fields

Modifier and Type	Field	Description
final double	bic	The BIC score when the distribution is fit on a sample data.
final double	L	The log-likelihood when the distribution is fit on a sample data.

Fields inherited from class smile.stat.distribution.DiscreteMixture

components

Constructor Summary

Constructors

Constructor	Description
DiscreteExponentialFamilyMixture(DiscreteMixture.Component... mixture)	Constructor.

Method Summary

Modifier and Type	Method	Description
static DiscreteExponentialFamilyMixture	fit(int[] x, DiscreteMixture.Component... components)	Fits the mixture model with the EM algorithm.
static DiscreteExponentialFamilyMixture	fit(int[] x, DiscreteMixture.Component[] components, double gamma, int maxIter, double tol)	Fits the mixture model with the EM algorithm.

Methods inherited from class smile.stat.distribution.DiscreteMixture

bic, cdf, entropy, length, logp, map, mean, p, posteriori, quantile, rand, size, toString, variance

Methods inherited from class smile.stat.distribution.DiscreteDistribution

likelihood, logLikelihood, logp, p, quantile, randi, randi

Methods inherited from class smile.stat.distribution.AbstractDistribution

inverseTransformSampling, quantile, quantile, rejection

Methods inherited from class java.lang.Object

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

Methods inherited from interface smile.stat.distribution.Distribution

likelihood, logLikelihood, rand, sd

Field Details

L

public final double L

The log-likelihood when the distribution is fit on a sample data.

bic

public final double bic

The BIC score when the distribution is fit on a sample data.

Constructor Details

DiscreteExponentialFamilyMixture

public DiscreteExponentialFamilyMixture(DiscreteMixture.Component... mixture)

Constructor.

Parameters:

mixture - a list of discrete exponential family distributions.

Method Details

fit

public static DiscreteExponentialFamilyMixture fit(int[] x,
 DiscreteMixture.Component... components)

Fits the mixture model with the EM algorithm.

Parameters:

components - the initial configuration of mixture. Components may have different distribution form.

x - the training data.

Returns:

the distribution.

fit

public static DiscreteExponentialFamilyMixture fit(int[] x,
 DiscreteMixture.Component[] components,
 double gamma,
 int maxIter,
 double tol)

Fits the mixture model with the EM algorithm.

Parameters:

components - the initial configuration.

x - the training data.

gamma - the regularization parameter.

maxIter - the maximum number of iterations.

tol - the tolerance of convergence test.

Returns:

the distribution.