This function fits a HMM to `fHMM_data`

via numerical likelihood
maximization.

## Usage

```
fit_model(data, ncluster = 1, seed = NULL, verbose = TRUE, init = NULL)
# S3 method for fHMM_model
print(x, ...)
```

## Arguments

- data
An object of class

`fHMM_data`

.- ncluster
Set the number of clusters for parallelization. By default,

`ncluster = 1`

.- seed
Set a seed for the sampling of initial values. No seed by default.

- 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`

.- x
An object of class

`fHMM_model`

.- ...
Currently not used.

## Value

An object of class `fHMM_model`

.