This function fits a HMM to `data`

via maximum likelihood estimation.

## 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`

.