move.HSMM.simulate: Simulate data from a hidden semi markov model
In benaug/move.HMM: Fit HMM and HSMM animal movement models

This function simulates data from a user-specified hidden semi markov model

1 2	move.HSMM.simulate(dists, params, n, nstates, delta = NULL)

`dists`	A vector of distributions of length ndist+1, with the first distribution chosen from: shiftpois, shiftnegbin The following distribution(s) are from the following list: weibull, gamma, exponential, normal, lognormal, lnorm3, posnorm, invgamma, rayleigh, f, ncf, dagum, frechet, beta, binom, poisson, nbinom, zapois, wrpcauchy, wrpnorm.
`params`	a list of starting parameter values. If nstates=2, params is of length ndist+1 The first element of the list must be the starting values for the dwell time distribution. If any distributions only have 1 parameter, the list entry must be a nstates x 1 matrix. If nstates>2, params is of lenght ndist+2, with the first element being the starting values for the t.p.m., the second element being the starting values for the dwell time distribution, and the following element(s) being the starting values for the observation distributions
`n`	The length of the hidden markov model to be simulated
`nstates`	The number of hidden states
`delta`	an optional vector of starting state probabilities. If no vector is supplied, the stationary distribution is used.