Group HMM Algorithms
Algorithms on HmmGraph objects.

Grouped Function Overview

Grouped Functions Detail

TCargo backwardAlgorithm(hmm, seq);

Defined in
<seqan/graph_algorithms.h>
Given a Hidden Markov Model hmm, the backward algorithm computes the probability of the sequence seq.

Parameters

hmm The HmmGraph with the HMM to use.
seq Input sequence to use in the backward algorithm.

Returns

TCargo The probability of the sequence seq. TProbability is the type parameter TCargo of the type of hmm.

See the Wikipedia article on the Forward-backward algorithm for an introduction to the algorithm itself.

Data Races

Thread safety unknown!

See Also

TCargo forwardAlgorithm(hmm, seq);

Defined in
<seqan/graph_algorithms.h>
Given a Hidden Markov Model hmm, the forward algorithm computes the probability of the sequence seq.

Parameters

hmm The HmmGraph with the HMM to use.
seq Input sequence to use in the forward algorithm.

Returns

TProbability The probability of the sequence seq. TProbability is the type parameter TCargo of the type of hmm.

Remarks

See the Wikipedia article on the Forward algorithm for an introduction to the algorithm itself.

Data Races

Thread safety unknown!

See Also

void generateSequence(hmm, seq, states, numSeq, maxLen);

Defined in
<seqan/graph_algorithms.h>
Generates random state and alphabet sequence of a given HMM.

Parameters

seq A StringSet of alphabet sequences.
states A ContainerConcept object of state sequences.
hmm The HmmGraph to use.
numSeq The number of sequences to generate.
maxLen The maximum length of the sequences. The sequences might be shorter if the ends tate is reached before maxLen.

Remarks

Because of silent states, generated alphabet and state sequences might have different lengths.

Data Races

Thread safety unknown!

TCargo viterbiAlgorithm(path, hmm, seq);

Defined in
<seqan/graph_algorithms.h>
Implements the Viterbi algorithm for Hidden Markov Models.

Parameters

path The state path; String of vertex descriptors.
hmm The HmmGraph to use.
seq Input sequence.

Returns

TCargo Probability of the path, the type parameter TCargo from type of hmm.

The Viterbi algorithm computes the most likely sequence of hidden states of the Hidden Markov Model hmm given the sequence seq using dynamic programming. The result is the most likely sequence of hidden states and returned in path.

Remarks

See the Wikipedia article on the Viterbi algorithm for an introduction to the algorithm itself.

Data Races

Thread safety unknown!

See Also