getLogLik: Calculate log likelihood state distribution.

In STAN: The Genomic STate ANnotation Package

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

STAN documentation built on Nov. 8, 2020, 11:11 p.m.