de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
Interface SamplingState

All Superinterfaces:

SamplingComponent, SamplingFromStatistic, State, TrainableState

All Known Implementing Classes:

SimpleSamplingState

public interface SamplingState
extends TrainableState, SamplingFromStatistic

Author:

Jens Keilwagen

Method Summary

double

getLogGammaScoreForCurrentStatistic() This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.TrainableState

addToStatistic

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State

getGraphvizNodeOptions, getLogScoreFor, isSilent

Methods inherited from interface de.jstacs.sampling.SamplingFromStatistic

drawParametersFromStatistic, getLogPosteriorFromStatistic

Methods inherited from interface de.jstacs.sampling.SamplingComponent

acceptParameters, extendSampling, initForSampling, isInSamplingMode, parseNextParameterSet, parseParameterSet, samplingStopped

Method Detail

getLogGammaScoreForCurrentStatistic

double getLogGammaScoreForCurrentStatistic()

This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics

Returns:

the logarithm of the gamma-score for the current statistics