Skip to contents

This function fits a HMM to data via maximum likelihood estimation.

Usage

fit_model(data, ncluster = 1, seed = NULL, verbose = TRUE, init = NULL)

Arguments

data

An object of class fHMM_data.

ncluster

Set the number of clusters for parallelization.

seed

Set a seed for the sampling of initial values.

verbose

Set to TRUE to print progress messages.

init

Optionally an object of class parUncon for initialization. This can for example be the estimate of a previously fitted model model, i.e. the element model$estimate. The initial values are computed via replicate(n, jitter(init, amount = 1), simplify = FALSE), where n <- data$controls$fit$runs.

Value

An object of class fHMM_model.

Details

The function is parallelized only if ncluster > 1.