prior:: transInit object; model for the prior probabilities, also unconditional probabilities
dens:: Array of dimension sum(ntimes)nrespnstates providing the densities of the observed responses for each state.
init:: Array of dimension length(ntimes)*nstates with the current predictions for the initial state probabilities.
nstates:: The number of states (classes) of the model.
nresp:: The number of independent responses.
ntimes:: A vector of 1's for each case; for internal use.
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.
Accessor Functions
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.