gam0_fit_hmm: Fit an HMM
In simonecollier/lizardHMM: Fitting Lizard Movement Data with HMMs

This function fits data with an HMM by maximizing the likelihood estimate given initial gamma parameters.

gam0_fit_hmm(
  x,
  design,
  num_states,
  num_variables,
  num_subjects,
  num_covariates,
  alpha0,
  theta0,
  zweight0,
  beta0,
  delta0,
  state_dep_dist_pooled = FALSE,
  iterlim = 100,
  steptol = 1e-06,
  hessian = FALSE,
  print.level = 0
)

`x`	The data to be fit with an HMM in the form of a 3D array. The first index (row) corresponds to time, the second (column) to the variable number, and the third (matrix number) to the subject number.
`design`	A list of design matrices for each subject with each row indicating the time and each column indicating the value of the covariate.
`num_states`	The number of states in the desired HMM.
`num_variables`	The number of variables in the data.
`num_subjects`	The number of subjects/trials that generated the data.
`num_covariates`	The number of covariates in the data that the transition probability matrix depends on.
`alpha0`	The starting values for the means of the gamma distributed state dependent distributions of the HMM. `alpha0` is a list of matrices, each matrix corresponding to a different variable in the data being fit. The columns of the matrices correspond to the state number and the rows correspond to the subject number.
`theta0`	The starting values for the standard deviations of the gamma distributed state dependent distributions of the HMM. `theta0` is a list of matrices, each matrix corresponding to a different variable in the data being fit. The columns of the matrices correspond to the state number and the rows correspond to the subject number.
`beta0`	A matrix of the initial regression coefficients for the effect of the covariates on the transition probability matrices `gamma`.
`delta0`	A list with each element being the starting initial state distribution vector of the HMM for the subject corresponding to that index.
`state_dep_dist_pooled`	A logical variable indiacting whether the state dependent distribution parameters `alpha` and `theta` should be treated as equal for all subjects.
`iterlim`	A value indicating the number of iterations `nlm()` should run before exiting.
`hessian`	A logical variable indicating whether to compute the hessian at the minimum.
`@param`	zweight0 The starting values for the weights of the zero inflated portion of the gamma distributions. `zweight0` is a list of vectors, one for each variable, and each vector element correspomnds to a different subject.