# Two sequences, one HMM

I know how to fit a hidden markov model to a data sequence, using the matlab-implementation of the baum-welch algorithm.

But what should I do if I do not have one data sequence, but a bunch of them? How can I fit to a set of sequences?

I think what I want to do is to maximize the likelihood of the HMM to output any of my sequences.

Is there a best practice for that kind of problem?

• if you are willing to look at R, to my understanding, the depmixS4 package may be able to handle this. See here for the paper: jstatsoft.org/v36/i07 Apr 27 '13 at 23:03
• I am bound to matlab in my current project. Anyways, I found a nice implementation for matlab.. But thanks for your comment, other might need the info! Apr 27 '13 at 23:22