com.numericalmethod.suanshu.stats.hmm.mixture.distribution

Class LogNormalDistribution

java.lang.Object

com.numericalmethod.suanshu.stats.hmm.mixture.distribution.LogNormalDistribution

All Implemented Interfaces:

HMMDistribution, java.io.Serializable

public class LogNormalDistribution
extends java.lang.Object
implements HMMDistribution

The HMM states use the Log-Normal distribution to model the observations.

See Also:

LogNormalDistribution, Wikipedia: Log-normal distribution, Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	LogNormalDistribution.Lambda the Log-Normal distribution parameters

Constructor Summary

Constructors

Constructor and Description
LogNormalDistribution(LogNormalDistribution.Lambda[] lambda) Construct a Log-Normal distribution for each state in the HMM model.
LogNormalDistribution(LogNormalDistribution.Lambda[] lambda, boolean isMuEstimated, boolean isSigmaEstimated) Construct a Log-Normal distribution for each state in the HMM model.

Method Summary

Modifier and Type	Method and Description
ProbabilityDistribution[]	getDistributions() Get the distributions (possibly differently parameterized) for all states.
LogNormalDistribution.Lambda[]	getMStepParams(double[] observations, Matrix u, java.lang.Object[] param0) Maximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.
LogNormalDistribution.Lambda[]	getParams() Get the parameters, for each state, of the distribution.
RandomNumberGenerator[]	getRandomNumberGenerators() Get the random number generators corresponding to the distributions (possibly differently parameterized) for all states.
HMMDistribution	newEMDistribution(java.lang.Object[] param) Construct a new distribution from a set of parameters, one set per state.

Methods inherited from class java.lang.Object

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

Constructor Detail

LogNormalDistribution

public LogNormalDistribution(LogNormalDistribution.Lambda[] lambda,
                             boolean isMuEstimated,
                             boolean isSigmaEstimated)

Construct a Log-Normal distribution for each state in the HMM model.

Parameters:

lambda - the distribution parameters

isMuEstimated - indicate whether parameter mu is to be estimated

isSigmaEstimated - indicate whether parameter sigma is to be estimated

LogNormalDistribution

public LogNormalDistribution(LogNormalDistribution.Lambda[] lambda)

Construct a Log-Normal distribution for each state in the HMM model.

Parameters:

lambda - the distribution parameters

Method Detail

getParams

public LogNormalDistribution.Lambda[] getParams()

Description copied from interface: HMMDistribution

Get the parameters, for each state, of the distribution.

Specified by:

getParams in interface HMMDistribution

Returns:

the parameters, for each state, of the distribution

getRandomNumberGenerators

public RandomNumberGenerator[] getRandomNumberGenerators()

Description copied from interface: HMMDistribution

Get the random number generators corresponding to the distributions (possibly differently parameterized) for all states.

Specified by:

getRandomNumberGenerators in interface HMMDistribution

Returns:

the random number generators corresponding to the distributions

getDistributions

public ProbabilityDistribution[] getDistributions()

Description copied from interface: HMMDistribution

Get the distributions (possibly differently parameterized) for all states.

Specified by:

getDistributions in interface HMMDistribution

Returns:

the distributions

getMStepParams

public LogNormalDistribution.Lambda[] getMStepParams(double[] observations,
                                                     Matrix u,
                                                     java.lang.Object[] param0)

Description copied from interface: HMMDistribution

Maximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.

Specified by:

getMStepParams in interface HMMDistribution

Parameters:

observations - the observations

u - this is a log-transformed version of eq. (4.13) of Zucchini and MacDonald (2009), p. 65

param0 - the current estimators of the distribution parameters

Returns:

the MLE estimators

newEMDistribution

public HMMDistribution newEMDistribution(java.lang.Object[] param)

Description copied from interface: HMMDistribution

Construct a new distribution from a set of parameters, one set per state.

Specified by:

newEMDistribution in interface HMMDistribution

Parameters:

param - the parameters of the distribution, one set per state

Returns:

a new HMM distribution