I am running a Baum-Welch HMM algorithm (in R). The sequence vector contains a series of observations which have been gathered from a dataset where the data has 17 states.
I can successfully run the HMM algorithm and it converges without any problems when I set pseudo count to 1e-09, below that the algorithm fails.
My question relates to the Baum-Welch algorithm and local minima. When I run the algorithm and obtain the estimates for the emission matrix and transition matrix, I then use these as inputs to calculate the posterior probability of a sequence.
That is all fine except that when I redo all of the above (in a new R session) I get completely different posterior probability estimates. Is this because the BW algorithm is getting stuck in different local minima each time?