Re: [R] Bayesian Hidden Markov Models
Dear James,
The distances are normalized between zero and 1, so in your case all of them
will be zero. You can check that with
res$Dist.for.model
And do
Q.NH(summary(res)[[1]]$beta, x=0)
To obtain the common transition matrix.
Cheers,
Oscar
On 29/2/12 03:59, monkeylan lanjin...@yahoo.com.cn wrote:
Dear Oscar,
I am extremely grateful to your help and detailed explanation of the use of
RJaCGH package.
But, when runing the sample codes you listed, another issue I am a little
confused is as following:
After runing summary(res), I have got the estimation of the random matrix
Beta:
Parameters of the transition functions:
Normal Gain
Normal 0.000 4.258
Gain2.001 0.000
But, the transition probabilty matrix Q based on the aboving Beta is more
concerned in my modeling.
Here, I am not sure how can I get the matrix Q. I did try the Q.NH
functions.However, Shoud I set the distance parameter x be 1 or 0? I am not
sure.
If 1( according to my own understanding), the following result seems not
reseanable.
tran-matrix(c(0,2.001,4.528,0),2,2)
Q.NH(beta=tran, x=1)
[,1] [,2]
[1,] 0.5 0.5
[2,] 0.5 0.5
Many thanks for your further help and time.
James Allan
--- 12年2月28日，周二, Oscar Rueda [via R]
ml-node+s789695n4427760...@n4.nabble.com 写道：
发件人: Oscar Rueda [via R] ml-node+s789695n4427760...@n4.nabble.com
主题: Re: Bayesian Hidden Markov Models
收件人: monkeylan lanjin...@yahoo.com.cn
日期: 2012年2月28日,周二,下午7:02
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 [hidden email] 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]
[hidden email] 写道：
发件人: Oscar Rueda [via R] [hidden email]
主题: Re: Bayesian Hidden Markov Models
收件人: monkeylan [hidden email]
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-tp4423946p442394
6
.
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
Re: [R] Bayesian Hidden Markov Models
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 lanjin...@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+s789695n4424152...@n4.nabble.com 写道：
发件人: Oscar Rueda [via R] ml-node+s789695n4424152...@n4.nabble.com
主题: Re: Bayesian Hidden Markov Models
收件人: monkeylan lanjin...@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
.
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-tp4423946p44
24152.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]]
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 the above-named
person(s). If you are not the intended recipient, notify the sender
immediately, delete this email from your system and do not disclose or use for
any purpose.
We may monitor all incoming and outgoing emails in line with current
legislation. We have taken steps to ensure that this email and attachments are
free from any virus, but it remains your responsibility to ensure that viruses
do not adversely affect you.
Cancer Research UK
Registered in England and Wales
Company Registered Number: 4325234.
Registered Charity Number: 1089464 and Scotland SC041666
Registered Office Address: Angel Building, 407 St John Street, London EC1V 4AD.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
Re: [R] Bayesian Hidden Markov Models
Dear Oscar,
Â
I am extremely grateful to your help and detailed explanation of the use of
RJaCGH package.
But, when runing the sample codes you listed, another issue I am a little
confused is as following:
After runing summary(res), I have got the estimation of the random matrix Beta:
Parameters of the transition functions:
      Normal Gain
Normal 0.000 4.258
Gain   2.001 0.000
Â
But, the transition probabilty matrix Q based on the aboving Beta is more
concerned in my modeling.
Here, I am not sure how can I get the matrix Q. I did try the Q.NH
functions.However, Shoud I set the distance parameter x be 1 or 0? I am not
sure.
Â
 If 1( according to my own understanding), the following result seems not
reseanable.
Â
tran-matrix(c(0,2.001,4.528,0),2,2)
Q.NH(beta=tran, x=1)
    [,1] [,2]
[1,]Â 0.5Â 0.5
[2,]Â 0.5Â 0.5
Â
Many thanks for your further help and time.
Â
James Allan
--- 12å¹´2æ28æ¥ï¼å¨äº, Oscar Rueda [via R]
ml-node+s789695n4427760...@n4.nabble.com åéï¼
å件人: Oscar Rueda [via R] ml-node+s789695n4427760...@n4.nabble.com
主é¢: Re: Bayesian Hidden Markov Models
æ¶ä»¶äºº: monkeylan lanjin...@yahoo.com.cn
æ¥æ: 2012å¹´2æ28æ¥,å¨äº,ä¸å7:02
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
Â
On 28/2/12 04:52, monkeylan [hidden email] wrote:
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.
Â
So, Could you please tell me how can I adjust the R functions in your package
to implement my analysis?
Â
Best Regards,
Â
James Allan
--- 12å¹´2æ27æ¥ï¼å¨ä¸, Oscar Rueda [via R]
[hidden email] åéï¼
å件人: Oscar Rueda [via R] [hidden email]
主é¢: Re: Bayesian Hidden Markov Models
æ¶ä»¶äºº: monkeylan [hidden email]
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-tp4423946p44
24152.html
To unsubscribe from Bayesian Hidden Markov Models, click here.
NAML
--
View this message in
[R] Bayesian Hidden Markov Models
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. __ 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.
Re: [R] Bayesian Hidden Markov Models
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 lanjin...@yahoo.com.cn 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.
__
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.
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}}
__
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.
Re: [R] Bayesian Hidden Markov Models
Dear Oscar,
Â
I really appreciate your help for my problem. I have taken a look at the R
package RJaCGH you mentioned roughly, but I am really a little confused by the
CGH microarrays background of the package. Actually, I am a graduate student,
majoring Mathematical Statistics. So, I know nothing about the CGH microarrays.
Â
Have you ever used the RJaCGH package before? If so, could you please briefly
tell me how to use RJaCGH to implement a Bayesian Hidden Markov Models for my
univariate time series?
Â
Thanks again for your patience and time.
Â
Best Regards,
Â
James Allan
Â
--- 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-tp4423946p4426601.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.
Re: [R] Bayesian Hidden Markov Models
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.
Â
So, Could you please tell me how can I adjust the R functions in your package
to implement my analysis?
Â
Best Regards,
Â
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.
