Maura,

On Nov 14, 2008, at 2:40 PM, <mauede@alice.it> <mauede@alice.it> wrote:

> How can I access the depmix-intro vignette ?
> I have displayed thhttp://cat.inist.fr/? 
> aModele=afficheN&cpsidt=18787092e R vignette but depmix does no  
> appear in the list.
> I do need to go throusg some worked out example to see if it can be  
> used for  the respiraton model.
>
the depmix-intro.pdf is in the doc directory of the package

>
> Why I get the following messages when I type :
> > library(depmix)
>
> Warning messages:
>
> 1: dependency ‘Rdonlp2’ is not available
> 2: dependency ‘Rdonlp2’ is not available
> 3: dependency ‘Rdonlp2’ is not available
>
i think you need the depmixS4 package which is different from depmix.
Rdonlp is not neccessary but does enhance the functionality of depmixS4

hth, Ingmar

>
> Thank you in advance,
> Maura
>
> http://cat.inist.fr/?aModele=afficheN&cpsidt=18787092
> -----Messaggio originale-----
> Da: r-help-bounces@r-project.org per conto di Ingmar Visser
> Inviato: mer 12/11/2008 15.10
> A: Maura E Monville
> Cc: r-help@r-project.org
> Oggetto: Re: [R] choice of an HMM package
>
> Dear Maura,
>
> On 9 Nov 2008, at 02:24, Maura E Monville wrote:
>
> > 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.
>
> ?depmixS4 provides a brief overvied of the package
> ?depmix  tells you how to specify models
> ?fit tells you how to fit specified models
>
> The package also includes a vignette depmix-intro.pdf with some worked
> examples.
>
> > 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.
>
> As the documentation says depmixS4 also fits non-dependent mixtures,
> however that
> does not seem applicable in your case as you want to model time
> series with HMMs.
> There is no principled limitation in the lengths of timeseries
> depmixS4 can handle.
>
> > 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.
>
> Can you provide a reference for this kind of model as that will make
> your question
> much more clear.
>
> > Any suggestion from HMM experts is welcome.
> >
> > Best regards,
> >
> > --
> > Maura E.M
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> Ingmar Visser
> Department of Psychology, University of Amsterdam
> Roetersstraat 15
> 1018 WB Amsterdam
> The Netherlands
> t: +31-20-5256723
>
>
>
>         [[alternative HTML version deleted]]
>
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