A `depmix.sim`

model. The `depmix.sim`

class directly
extends the `depmix`

class, and has an additional slot for the
true states. A `depmix.sim`

model can be generated by
`simulate(mod,...)`

, where `mod`

is a `depmix`

model.

`response`

:List of list of

`response`

objects.`transition`

List of

`transInit`

objects.`prior`

:`transInit`

object.`dens`

:Array of dimension sum(ntimes)*nresp*nstates providing the densities of the observed responses for each state.

`trDens`

:Array of dimension

`sum(ntimes)`

*nstates providing the probability of a state transition depending on the predictors.`init`

:Array of dimension

`length(ntimes)`

*nstates with the current predictions for the initial state probabilities.`homogeneous`

:Logical indicating whether the transitions are time-dependent or not; for internal use.

`ntimes`

:A vector containing the lengths of independent time series; if data is provided, sum(ntimes) must be equal to nrow(data).

`nstates`

:The number of states of the model.

`nresp`

:The number of independent responses.

`npars`

:The total number of parameters of the model. This is not the degrees of freedom, ie there are redundancies in the parameters, in particular in the multinomial models for the transitions and prior.

`states`

:A matrix with the true states.

The following functions should be used for accessing the corresponding slots:

`npar`

:The number of parameters of the model.

`nresp`

:The number of responses.

`nstates`

:The number of states.

`ntimes`

:The vector of independent time series lengths.

Maarten Speekenbrink

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