STAN (version 2.0.3)

getLogLik: Calculate log likelihood state distribution.

Description

The function calculates log likelihood for one or more observation sequence.

Usage

getLogLik(hmm, obs = list(), emissionProbs = list(), dirFlags = list(), verbose = FALSE, nCores = 1, sizeFactors=matrix(1, nrow=length(obs), ncol=ncol(obs[[1]])))#'

Arguments

hmm

The Hidden Markov Model.

obs

The observations. A list of one or more entries containing the observation matrix (numeric) for the samples (e.g. chromosomes).

emissionProbs

List of precalculated emission probabilities of emission function is of type 'null'.

dirFlags

The flag sequence is needed when a bdHMM is fitted on undirected data (e.g.) ChIP only. It is a list of character vectors indication for each position its knwon directionality. U allows all states. F allows undirected states and states in forward direction. R allows undirected states and states in reverse direction.

verbose

logical for printing algorithm status or not.

nCores

Number of cores to use for computations.

sizeFactors

Library size factors for Emissions PoissonLogNormal or NegativeBinomial as a length(obs) x ncol(obs[[1]]) matrix.

Value

The log likelihood of the observations sequences, given the model.

See Also

HMM

Examples

data(example)
hmm_ex = initHMM(observations, nStates=3, method="Gaussian") 
hmm_fitted = fitHMM(observations, hmm_ex)
loglik = getLogLik(hmm_fitted, observations)
loglik