[R] Help with kalman-filterd betas using the dlm package

[spencerg]

      1.  Might you look again at section "2.  Maximum likelihood 
estimation" of the "dlm" vignette?  It describes how to estimate 
parameters. 


      2.  Have you started with the code on those 2 pages, confirming 
that you can make that work and understand what it does?  If yes, then 
try to build code for your problem as a series of small modifications to 
that example.  With luck, this will bring enlightenment.  If not, try to 
express your question in terms of commented, minimal, self-contained 
code that others can copy into R to replicate what you see then modify 
to get it to work, as suggested in the posting guide 
"www.R-project.org/posting-guide.html".  If someone reading this list 
can do this in a few seconds, it will increases the chances that you 
will get a useful reply. 


      Hope this helps. 
      Spencer Graves           

tom81 wrote:
> I have studied both the vinguette and other material I've been able to get my
> hands on and Im starting to get a better understanding. And I'm defenitly
> going to buy Petris, Petrone, and Campagnoli (2009) Dynamic Linear Models
> with R. But that's not publish yet so I 'm not getting much help there.
>
> This is the set-up i am using
> y[t] = a[t] + b*x[t] + V[t],  
> a[t] = a[t-1] + W[t,a] 
> b[t] = b[t-1] + W[t,b]
>
> V[t] ~ N(0,V)
> W[t] ~ N(0,W)
> W = blockdiag(W[a],W[b])
>
>
> V could be estimated from the data with a non-diagonal variance matrix of
> the returns,
> W would be the same estimated in the same way but where the effect of past
> betas in the transition taken into account. But how do I estimate that
> matrix, is that done with a MLE,SUR or some other statistical teqnique.
>
> Im also assuming in this example that a[t] are time invariant, which gives
> W[a] = 0
>
> Appriciate any guidence.
> Regards Tom
> "
>
> spencerg wrote:
>   
>>       Have you worked through "vignette('dlm')"?  Vignettes are nice 
>> because they provide an Adobe Acrobat Portable Document Format (pdf) 
>> file with a companion R script file, which you can get as follows: 
>>
>>
>> (dlm. <- vignette('dlm'))
>> Stangle(dlm.$file) 
>>
>>
>>       The first of these two lines opens the "pdf" file.  The second 
>> creates a file "dlm.R" in the working directory (getwd()) containing the 
>> R commands discussed in the "pdf" file. 
>>
>>
>>       If I remember correctly, your question is answered in this vignette. 
>>
>>
>>       You may also be interested in a book that is soon to appear about 
>> this package:  Petris, Petrone, and Campagnoli (2009) Dynamic Linear 
>> Models with R (Springer;  
>> http://www.amazon.com/Dynamic-Linear-Models-R-Use/dp/0387772375/ref=sr_1_4?ie=UTF8&s=books&qid=1242162708&sr=1-4), 
>> scheduled to ship in late June.  If you have long-term interest in this 
>> subject, as I suspect you may, you might find this book interesting and 
>> useful. 
>>
>>
>>       Hope this helps.
>>       Spencer Graves
>> "
>> tom81 wrote:
>>     
>>> Hi all R gurus out there, 
>>> Im a kind of newbie to kalman-filters after some research I have found
>>> that
>>> the dlm package is the easiest to start with. So be patient if some of my
>>> questions are too basic.
>>>
>>> I would like to set up a beta estimation between an asset and a market
>>> index
>>> using a kalman-filter. Much littarture says it gives superior estimates
>>> compared to OLS estimates. So I would like to learn and to use the
>>> filter.
>>>
>>> I would like to run two types of kalman-filters, one with using a
>>> random-walk model (RW) and one with a stationary model, in other worlds
>>> the
>>> transition equition either follow a RW or AR(1) model.
>>>
>>> This is how I think it would be set up;
>>>
>>> I will have my time-series Y,X, where Y is the response variable
>>>
>>> this setup should give me a RW process if I have understood the example
>>> correctly
>>> mydlmModel = dlmModReg(X)  + dlmModPoly(order=1)
>>>
>>> and then run on the dlm model
>>> dlmFilter(Y,mydlmModel )
>>>
>>> but setting up a AR(1) process is unclear, should I use dlmModPoly or the
>>> dlmModARMA to set up the model.
>>>
>>> And at last but not the least, how do I set up a proper build function to
>>> use with dlmMLE to optimize the starting values.
>>>
>>> Regards Tom
>>>
>>>       
>> ______________________________________________
>> R-help at 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.
>>
>>
>>     
>
>