getLogLik {STAN} | R Documentation

## 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

[Package STAN version 2.20.0 Index]