state space model for poisson distribution

classic Classic list List threaded Threaded
2 messages Options
Reply | Threaded
Open this post in threaded view
|

state space model for poisson distribution

arun kirshna
Hi Rers,

I have a poission time series model with 5 parameters.   I just wanted to  remove two  of the lag on response in the model and put it as a system model.  I am not sure about the codes to combine these  two on R.  If anybody has any R example (code), please post it.

My original model: log(Y(t))~constant+b1*Y(t-1)+b2*Y(t-2)+b3*(variable1)+b4*(variable2)+e
I would like to construct a model:
log(Y(t))~constant+b1*(variable1)+b2*(variable2)+X(t)

X(t)~phi1*Xt-1+phi2*Xt-2+error

where X(t) is the autoregressive lag effect of response.

A.K.




       
---------------------------------

        [[alternative HTML version deleted]]

______________________________________________
[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.
Reply | Threaded
Open this post in threaded view
|

Re: state space model for poisson distribution

Spencer Graves
      Have you looked at the 'sspir' package?  A good introduction to
the package can be found in C. Dethlefsen and S. Lundbye-Christensen
(2006) "Formulating state space models in r with focus on longitudinal
regression models", Journal of Statistical Software, 16(1)
[http://www.jstatsoft.org/v16/i01]

      Hope this helps.
      Spencer Graves  

arun kirshna wrote:

> Hi Rers,
>
> I have a poission time series model with 5 parameters.   I just wanted to  remove two  of the lag on response in the model and put it as a system model.  I am not sure about the codes to combine these  two on R.  If anybody has any R example (code), please post it.
>
> My original model: log(Y(t))~constant+b1*Y(t-1)+b2*Y(t-2)+b3*(variable1)+b4*(variable2)+e
> I would like to construct a model:
> log(Y(t))~constant+b1*(variable1)+b2*(variable2)+X(t)
>
> X(t)~phi1*Xt-1+phi2*Xt-2+error
>
> where X(t) is the autoregressive lag effect of response.
>
> A.K.
>
>
>
>
>        
> ---------------------------------
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [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.
>

______________________________________________
[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.