seq2hmm.ll

Compute the sequence-to-HMM likelihood of an HMM evaluated for a single
sequence and check if the sequence contains emissions that are not possible
according to the HMM. Auxiliary function used in <code>select.seeds</code>
and <code>assign.clusters</code>.

Provides an implementation of a mixture of hidden Markov models
(HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering
(DBHC) algorithm. The DBHC algorithm is an HMM Clustering
algorithm that finds a mixture of discrete-output HMMs while using
heuristics based on Bayesian Information Criterion (BIC) to search for the
optimal number of HMM states and the optimal number of clusters.

Gabriel Budel

DBHC

Sequence Clustering with Discrete-Output HMMs

seq2hmm.ll function

<dl><dt>hmm</dt>
<dd>An <code>hmm</code> object (see <code>build_hmm</code>)
containing a single sequence.</dd></dl>

Arguments

Sequence-to-HMM Likelihood — seq2hmm.ll

<dl>

<dt>hmm</dt>
<dd>An <code>hmm</code> object (see <code>build_hmm</code>)
containing a single sequence.</dd>

</dl>

seq2hmm.ll: Sequence-to-HMM Likelihood

Description

Usage

Value

Arguments

See Also