Description Usage Arguments Value
View source: R/move.HSMM.mllk.full.R
This function computes the negative log likelihood of the hidden Markov model. using all parameters, untransformed. It is used to get the covariance matrix of the fitted model.
1 2 | move.HSMM.mllk.full(parvect, obs, PDFs, CDFs, skeleton,
nstates, m1, ini, useRcpp = FALSE)
|
parvect |
The vector of parameters to be estimated |
obs |
A n x ndist matrix of data. If ndist=1, obs must be a n x 1 matrix. |
PDFs |
A list of PDFs for the dwell time and ndist observation distributions. |
CDFs |
A list of CDFs for the dwell time and ndist observation distributions. |
skeleton |
A list with the original parameter structure used to reassemble parvect |
nstates |
Number of hidden states |
m1 |
a vector of length nstates that specifies how many states will be used to approximate each state of the HSMM (see Langrock and Zuchinni 2011) |
ini |
numeric value that specifies how the initial state distribution is calculated. 0 sets the initial distribution to the stationary distribution. If this matrix is not invertible, 1 sets the initial distribution for each state within each state agreggate to 1/m(state). |
useRcpp |
Logical indicating whether or not to use Rcpp. |
The negative log likelihood of the hidden markov model.
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