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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