Class BetaMixtureDistribution
- java.lang.Object
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- dev.nm.stat.hmm.mixture.distribution.BetaMixtureDistribution
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- All Implemented Interfaces:
MixtureDistribution
public class BetaMixtureDistribution extends Object implements MixtureDistribution
The HMM states use the Beta distribution to model the observations.- See Also:
- dev.nm.stat.distribution.univariate.BetaDistribution
- ref/hmm/hmm_M_step1
- Wikipedia: Beta distribution
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
BetaMixtureDistribution.Lambda
the Beta distribution parameters
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Constructor Summary
Constructors Constructor Description BetaMixtureDistribution(BetaMixtureDistribution.Lambda[] lambda, boolean isAlphaEstimated, boolean isBetaEstimated, double epsilon, int maxIterations)
Constructs a Beta distribution for each state in the HMM model.BetaMixtureDistribution(BetaMixtureDistribution.Lambda[] lambda, int maxIterations)
Constructs a Beta distribution for each state in the HMM model.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description BetaMixtureDistribution.Lambda[]
getMStepParams(double[] observations, Vector[] u)
Maximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.BetaMixtureDistribution.Lambda[]
getParams()
Get the parameters, for each state, of the distribution.ProbabilityDistribution[]
newDistributions()
Get the distributions (possibly differently parameterized) for all states.MixtureDistribution
newMixtureDistribution(Object[] param)
Construct a new distribution from a set of parameters, one set per state.RandomNumberGenerator[]
newRandomNumberGenerators()
Get the random number generators corresponding to the distributions (possibly differently parameterized) for all states.
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Constructor Detail
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BetaMixtureDistribution
public BetaMixtureDistribution(BetaMixtureDistribution.Lambda[] lambda, boolean isAlphaEstimated, boolean isBetaEstimated, double epsilon, int maxIterations)
Constructs a Beta distribution for each state in the HMM model.- Parameters:
lambda
- the distribution parametersisAlphaEstimated
- indicate whether parameteralpha
is to be estimatedisBetaEstimated
- indicate whether parameterbeta
is to be estimatedepsilon
- a precision parameter: when a number |x| ≤ ε, it is considered 0maxIterations
- the maximum number of iterations in each M-step
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BetaMixtureDistribution
public BetaMixtureDistribution(BetaMixtureDistribution.Lambda[] lambda, int maxIterations)
Constructs a Beta distribution for each state in the HMM model.- Parameters:
lambda
- the distribution parametersmaxIterations
- the maximum number of iterations in each M-step
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Method Detail
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getParams
public BetaMixtureDistribution.Lambda[] getParams()
Description copied from interface:MixtureDistribution
Get the parameters, for each state, of the distribution.- Specified by:
getParams
in interfaceMixtureDistribution
- Returns:
- the parameters, for each state, of the distribution
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newRandomNumberGenerators
public RandomNumberGenerator[] newRandomNumberGenerators()
Description copied from interface:MixtureDistribution
Get the random number generators corresponding to the distributions (possibly differently parameterized) for all states.- Specified by:
newRandomNumberGenerators
in interfaceMixtureDistribution
- Returns:
- the random number generators corresponding to the distributions
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newDistributions
public ProbabilityDistribution[] newDistributions()
Description copied from interface:MixtureDistribution
Get the distributions (possibly differently parameterized) for all states.- Specified by:
newDistributions
in interfaceMixtureDistribution
- Returns:
- the distributions
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getMStepParams
public BetaMixtureDistribution.Lambda[] getMStepParams(double[] observations, Vector[] u)
Description copied from interface:MixtureDistribution
Maximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.- Specified by:
getMStepParams
in interfaceMixtureDistribution
- Parameters:
observations
- the observationsu
- this is in eq. (4.13) of Zucchini and MacDonald (2009), p. 65- Returns:
- the MLE estimators
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newMixtureDistribution
public MixtureDistribution newMixtureDistribution(Object[] param)
Description copied from interface:MixtureDistribution
Construct a new distribution from a set of parameters, one set per state.- Specified by:
newMixtureDistribution
in interfaceMixtureDistribution
- Parameters:
param
- the parameters of the distribution, one set per state- Returns:
- a new HMM distribution
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