Dear Doctor Oscar, Â 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 --- 12å¹´2æ27æ¥ï¼å¨ä¸, Oscar Rueda [via R] <ml-node+s789695n4424152...@n4.nabble.com> åéï¼ å件人: Oscar Rueda [via R] <ml-node+s789695n4424152...@n4.nabble.com> 主é¢: Re: Bayesian Hidden Markov Models æ¶ä»¶äºº: "monkeylan" <lanjin...@yahoo.com.cn> æ¥æ: 2012å¹´2æ27æ¥,å¨ä¸,ä¸å6:05 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. > > html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > [hidden email] 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. 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 NOTICE AND DISCLAIMER This e-mail (including any attachments) is intended for ...{{dropped:16}} ______________________________________________ [hidden email] 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. If you reply to this email, your message will be added to the discussion below:http://r.789695.n4.nabble.com/Bayesian-Hidden-Markov-Models-tp4423946p4424152.html To unsubscribe from Bayesian Hidden Markov Models, click here. NAML -- View this message in context: http://r.789695.n4.nabble.com/Bayesian-Hidden-Markov-Models-tp4423946p4427000.html Sent from the R help mailing list archive at Nabble.com. [[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.
