initHMM: Initialization of hidden Markov models

In STAN: The Genomic STate ANnotation Package

Description

Initialization of hidden Markov models

Usage

initHMM(obs, nStates, method, sizeFactors = matrix(1, nrow = length(obs), ncol = ncol(obs[[1]])), sharedCov = FALSE)

Arguments

obs	The observations. A list of one or more entries containing the observation matrix (numeric) for the samples (e.g. chromosomes).
nStates	The number of states.
method	Emission distribution of the model. One out of c("NegativeBinomial", "PoissonLogNormal", "NegativeMultinomial", "ZINegativeBinomial", "Poisson", "Bernoulli", "Gaussian", "IndependentGaussian")
sizeFactors	Library size factors for Emissions PoissonLogNormal or NegativeBinomial as a length(obs) x ncol(obs[[1]]) matrix.
sharedCov	If TRUE, (co-)variance of (Independent)Gaussian is shared over states. Only applicable to 'Gaussian' or 'IndependentGaussian' emissions. Default: FALSE.

Value

A HMM object.

Examples

data(example)
hmm_ex = initHMM(observations, nStates=3, method="Gaussian") 

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