Dear Edward,
Without knowing what you want exactly, it is basically impossible to help
you out.
The following code (with simulated data) works just fine. In what sense did
you not have success with HMM and/or depmixS4?
Best, Ingmar
library(HMM)
dat <- data.frame(Slide1_ACC=sample(c(0,1),100,rep=T
R Community -
I am attempting to fit a model as described in Hampton, Bossaerts, and
O'doherty (J. Neuroscience) 2006. They use a bayesian hidden markov model
to model the Reversal Learning data. I have tried using HMM and depmixS4
with no success. My data is a Reversal Learning Task in which t
ec 2008 22:15:13 -0200
>From: "Marcus Vinicius"
>Subject: [R] Hidden Markov Models.
>To: r-help@r-project.org
>Message-ID:
>
>Content-Type: text/plain
>Dear R user´s,
>Is there anyone that may send me articles, e-books or scripts (R/Matlab)
>about
Marcus Vinicius gmail.com> writes:
> Is there anyone that may send me articles, e-books or scripts (R/Matlab)
> about Hidden Markov Models?
You get a lot by searching R-project with the term "Hidden Markov", including a
package with that name.
Dieter
___
>
>
Dear R user´s,
Is there anyone that may send me articles, e-books or scripts (R/Matlab)
about Hidden Markov Models?
I would like studying this methodology.
Thanks a lot.
Best regards.
--
Prof. Marcus Vinicius P. de Souza
Juiz de Fora / MG
Brasil
[[alternative HTML version deleted]
I don't quite understand.
depmixS4 has no time series length constraints ...
best, Ingmar
> Thank you in advance for your attention.
>
> Kind regards,
> Maura Edelweiss
>
> -Messaggio originale-
> Da: Walter Zucchini [mailto:[EMAIL PROTECTED]
> Inviato: mar
getto: Re: R: Hidden Markov Models
Dear Ms Monville,
Hidden Markov models (HMMs), and that includes the msm implementation,
are not based on the assumption that the observations are independent.
Indeed HMMs are specifically designed to model serially dependent
observations. Of course that do
7 matches
Mail list logo
