[R] choice of an HMM package

From: Maura E Monville <maura.monville_at_gmail.com>
Date: Sun, 09 Nov 2008 02:24:23 +0100


We are trying to build a human respiration model. Preliminary analysis of some breathing signals has shown that humans breathe through switching among
a finite number of patterns.
Hidden Markov seems to be the right approach. Since most of our code is written in R scripting language, finding an R package implementing an HMM that we can use for our prototype would be very helpful. I have been suggested both *msm* and *depmixS4.* I have no previous experience with HMMs and feel at a loss about making a sensible choice.
As a novice I am more attracted by msm because of the comprehensive documentation, with worked out examples, that I am printing out. Whereas I could not find anything but the usual R function call description for depmixS4.
Moreover, I cannot make a sense of depmixS4 documentation mentioning time series of length 1 ... Does it mean depmixS4 models time series made up of one single observation ? Sorry for my trivial question.

In my case I have to model a variable which is an autocorrelated continuous function of time. The transition probabilities may as well depend on time. Therefore I believe we need an AutoRegressive Continuous Density HMM, possibly also non-stationary.
Any suggestion from HMM experts is welcome.

Best regards,

-- 
Maura E.M

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Received on Sun 09 Nov 2008 - 08:09:52 GMT

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