Uses of Class
de.jstacs.models.hmm.AbstractHMM

Packages that use AbstractHMM

de.jstacs.models.hmm	The package provides all interfaces and classes for a hidden Markov model (HMM).
de.jstacs.models.hmm.models	The package provides different implementations of hidden Markov models based on AbstractHMM

Uses of AbstractHMM in de.jstacs.models.hmm

Methods in de.jstacs.models.hmm that return AbstractHMM

AbstractHMM	AbstractHMM.clone()
static AbstractHMM	HMMFactory.createErgodicHMM(HMMTrainingParameterSet pars, int order, double ess, double selfTranistionPart, double expectedSequenceLength, Emission... emission) This method creates an ergodic, i.e. a completely connected, HMM using the given emissions.
static AbstractHMM	HMMFactory.createProfileHMM(MaxHMMTrainingParameterSet trainingParameterSet, double[][] initFromTo, boolean likelihood, int order, int numLayers, AlphabetContainer con, double ess, boolean conditionalMain, boolean closeCircle, double[][] conditionInitProbs) Creates a new profile HMM for a given architecture and number of layers.
static AbstractHMM	HMMFactory.createProfileHMM(MaxHMMTrainingParameterSet trainingParameterSet, HMMFactory.HMMType type, boolean likelihood, int order, int numLayers, AlphabetContainer con, double ess, boolean conditionalMain, boolean closeCircle, double[][] conditionInitProbs) Creates a new profile HMM for a given architecture and number of layers.
static AbstractHMM	HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, int... motifLength) This method creates a first order sunflower HMM.
static AbstractHMM	HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, PhyloTree[] t, double[] motifProb, int[] motifLength) This method creates a first order sunflower HMM allowing phylogenetic emissions.

Uses of AbstractHMM in de.jstacs.models.hmm.models

Subclasses of AbstractHMM in de.jstacs.models.hmm.models

class	DifferentiableHigherOrderHMM This class combines an HigherOrderHMM and a NormalizableScoringFunction by implementing some of the declared methods.
class	HigherOrderHMM This class implements a higher order hidden Markov model.
class	SamplingHigherOrderHMM
class	SamplingPhyloHMM This class implements an (higher order) HMM that contains multi-dimensional emissions described by a phylogenetic tree.