Class GammaMixtureDistribution
- java.lang.Object
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- dev.nm.stat.hmm.mixture.distribution.GammaMixtureDistribution
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- All Implemented Interfaces:
MixtureDistribution
public class GammaMixtureDistribution extends Object implements MixtureDistribution
The HMM states use the Gamma distribution to model the observations.- See Also:
- dev.nm.stat.distribution.univariate.GammaDistribution
- ref/hmm/hmm_M_step1
- Wikipedia: Gamma distribution distribution
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Nested Class Summary
Nested Classes Modifier and Type Class Description static classGammaMixtureDistribution.Lambdathe Gamma distribution parameters
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Constructor Summary
Constructors Constructor Description GammaMixtureDistribution(GammaMixtureDistribution.Lambda[] lambda, boolean isShapeEstimated, boolean isScaleEstimated, double epsilon, int maxIterations)Constructs a Gamma distribution for each state in the HMM model.GammaMixtureDistribution(GammaMixtureDistribution.Lambda[] lambda, int maxIterations)Constructs a Gamma 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 GammaMixtureDistribution.Lambda[]getMStepParams(double[] observations, Vector[] u)Maximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.GammaMixtureDistribution.Lambda[]getParams()Get the parameters, for each state, of the distribution.ProbabilityDistribution[]newDistributions()Get the distributions (possibly differently parameterized) for all states.MixtureDistributionnewMixtureDistribution(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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GammaMixtureDistribution
public GammaMixtureDistribution(GammaMixtureDistribution.Lambda[] lambda, boolean isShapeEstimated, boolean isScaleEstimated, double epsilon, int maxIterations)
Constructs a Gamma distribution for each state in the HMM model.- Parameters:
lambda- the distribution parametersisShapeEstimated- indicate whether the shape parameterkis to be estimatedisScaleEstimated- indicate whether the scale parameterthetais 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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GammaMixtureDistribution
public GammaMixtureDistribution(GammaMixtureDistribution.Lambda[] lambda, int maxIterations)
Constructs a Gamma 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 GammaMixtureDistribution.Lambda[] getParams()
Description copied from interface:MixtureDistributionGet the parameters, for each state, of the distribution.- Specified by:
getParamsin interfaceMixtureDistribution- Returns:
- the parameters, for each state, of the distribution
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newRandomNumberGenerators
public RandomNumberGenerator[] newRandomNumberGenerators()
Description copied from interface:MixtureDistributionGet the random number generators corresponding to the distributions (possibly differently parameterized) for all states.- Specified by:
newRandomNumberGeneratorsin interfaceMixtureDistribution- Returns:
- the random number generators corresponding to the distributions
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newDistributions
public ProbabilityDistribution[] newDistributions()
Description copied from interface:MixtureDistributionGet the distributions (possibly differently parameterized) for all states.- Specified by:
newDistributionsin interfaceMixtureDistribution- Returns:
- the distributions
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getMStepParams
public GammaMixtureDistribution.Lambda[] getMStepParams(double[] observations, Vector[] u)
Description copied from interface:MixtureDistributionMaximize, for each state, the log-likelihood of the distribution with respect to the observations and current estimators.- Specified by:
getMStepParamsin 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:MixtureDistributionConstruct a new distribution from a set of parameters, one set per state.- Specified by:
newMixtureDistributionin interfaceMixtureDistribution- Parameters:
param- the parameters of the distribution, one set per state- Returns:
- a new HMM distribution
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