This function constructs an object of class `fHMM_model`

, which
contains details about the fitted (hierarchical) Hidden Markov model.

## Usage

```
fHMM_model(
data,
estimate,
nlm_output,
estimation_time,
ll,
lls,
gradient,
hessian,
decoding
)
```

## Arguments

- data
An object of class

`fHMM_data`

.- estimate
A

`numeric`

vector of unconstrained model estimates.- nlm_output
The output of

`nlm`

for the selected optimization run.- estimation_time
A

`diff.time`

object, the total estimation time.- ll
A

`numeric`

, the model log-likelihood.- lls
A

`numeric`

vector, the model log-likelihoods in all optimization runs.- gradient
A

`numeric`

vector, the gradient at the optimum.- hessian
A

`matrix`

, the Hessian at the optimum.- decoding
A

`numeric`

vector, the decoded time series.