[R] Bayesian Hidden Markov Models

[Oscar Rueda]

Dear James, 

Basically you just need the values (y) and the positions (in your case it
would be the index of the times series). The chromosome argument does not
apply to your case so it can be a vector of ones.
If the positions are at the same distance between (equally spaced) then the
model will be homogeneous.

So for example something like this would be enough:
> library(RJaCGH)
> y <- c(rnorm(100,0,1), rnorm(20, 2, 1), rnorm(50, 0, 1))
> Pos <- 1:length(y)
> Chrom <- rep(1, length(y))
> res <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom)
> summary(res)

However, it uses a Reversible Jump algorithm and therefore jumps between
models with different hidden states. I would suggest you take a look at the
vignette that comes with the package or the paper that is referenced there
for specific details of the model it fits.


Hope it helps, 
Oscar 
 


On 28/2/12 04:52, "monkeylan" <lanjinchi at yahoo.com.cn> wrote:

> Dear Doctor Oscar,
>  
> Sorry for not noticing that you are the author of the RJaCGH package.
> 
> But I noticed that hidden Markov model in your package is with non-homogeneous
> transition probabilities. Here in my work, the HMM is just a first-order
> homogeneous Markov chain, i.e. the  transition  matrix is constant.
>  
> So, Could you please tell me how can I adjust the R functions in your package
> to implement my analysis?
>  
> Best Regards,
>  
> James Allan
> 
> 
> --- 12年2月27日，周一, Oscar Rueda [via R]
> <ml-node+s789695n4424152h18 at n4.nabble.com> 写道：
> 
> 
> 发件人: Oscar Rueda [via R] <ml-node+s789695n4424152h18 at n4.nabble.com>
> 主题: Re: Bayesian Hidden Markov Models
> 收件人: "monkeylan" <lanjinchi at yahoo.com.cn>
> 日期: 2012年2月27日,周一,下午6:05
> 
> 
> Dear James,
> Although designed for the analysis of copy number CGH microarrays, RJaCGH
> uses a Bayesian HMM model.
> 
> Cheers,
> Oscar
> 
> 
> On 27/2/12 08:32, "monkeylan" <[hidden email]> wrote:
> 
> 
>> Dear R buddies,
>> 
>> Recently, I attempt to model the US/RMB Exchange rate log-return time series
>> with a *Hidden Markov model (first order Markov Chain & mixed Normal
>> distributions). *
>> 
>> I have applied the RHmm package to accomplish this task, but the results are
>> not so satisfying.
>> So, I would like to try a *Bayesian method *for the parameter estimation of
>> the Hidden Markov model.
>> 
>> Could anyone kindly tell me which R package can perform Bayesian estimation
>> of the model?
>> 
>> Many thanks for your help and time.
>> 
>> Best Regards,
>> James Allan
>> 
>> 
>> --
>> View this message in context:
>> 
http://r.789695.n4.nabble.com/Bayesian-Hidden-Markov-Models-tp4423946p4423946>>
.
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>> Sent from the R help mailing list archive at Nabble.com.
>> 
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> Oscar M. Rueda, PhD.
> Postdoctoral Research Fellow, Breast Cancer Functional Genomics.
> Cancer Research UK Cambridge Research Institute.
> Li Ka Shing Centre, Robinson Way.
> Cambridge CB2 0RE
> England
> 
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Oscar M. Rueda, PhD.
Postdoctoral Research Fellow, Breast Cancer Functional Genomics.
Cancer Research UK Cambridge Research Institute.
Li Ka Shing Centre, Robinson Way.
Cambridge CB2 0RE 
England 




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