com.numericalmethod.suanshu.stats.hmm.mixture

Class HiddenMarkovModel

java.lang.Object

com.numericalmethod.suanshu.stats.markovchain.SimpleMC

com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

com.numericalmethod.suanshu.stats.hmm.mixture.HiddenMarkovModel

All Implemented Interfaces:

RandomNumberGenerator, java.io.Serializable

Direct Known Subclasses:

HmmBaumWelch

public class HiddenMarkovModel
extends HiddenMarkovModel

This is the mixture hidden Markov model (HMM). The observations are continuous and follow a continuous distribution.

See Also:

• W. Zucchini and I. L. MacDonald, "Hidden Markov Models for Time Series: An Introduction Using R," Boca Raton, Florida, CRC Press, 2009.
• Wikipedia: Hidden Markov model

, Serialized Form

Constructor Summary

Constructors

Constructor and Description
HiddenMarkovModel(HiddenMarkovModel model) Copy constructor.
HiddenMarkovModel(Vector PI, Matrix A, HMMDistribution dist) Construct a mixture hidden Markov model.

Method Summary

Modifier and Type	Method and Description
double	density(int state, double observation) Get the probability density of making an observation in a particular state.
HMMDistribution	getDistribution() Get the distribution in the hidden Markov model.

Methods inherited from class com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

next, nextDouble, seed

Methods inherited from class com.numericalmethod.suanshu.stats.markovchain.SimpleMC

A, bin, getStationaryProbabilities, nextState, nStates, PI

Methods inherited from class java.lang.Object

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

Constructor Detail

HiddenMarkovModel

public HiddenMarkovModel(Vector PI,
                         Matrix A,
                         HMMDistribution dist)

Construct a mixture hidden Markov model.

Parameters:

PI - the initial state probabilities

A - the state transition probabilities of the homogeneous hidden Markov chain

dist - the conditional distribution in the hidden Markov model

HiddenMarkovModel

public HiddenMarkovModel(HiddenMarkovModel model)

Copy constructor.

Parameters:

model - a HiddenMarkovModel

Method Detail

getDistribution

public HMMDistribution getDistribution()

Get the distribution in the hidden Markov model.

Returns:

the distribution in the hidden Markov model

density

public double density(int state,
                      double observation)

Get the probability density of making an observation in a particular state.

Parameters:

observation - the observation value

state - the hidden state label, counting from 1

Returns:

the probability density