[R-SIG-Finance] State Space Model + DLM Package in R

[nserdar]

Kalman filter approach is a special specification of  state space model.

This is Kalman Filter random walk process code in DLM packages: 

library(dlm) 

buildCAPM<-function(u){ 

        dlmModReg(rm,dV=exp(u[1]),dW=exp(u[2:3]))  # rm market 

} 

outMLE<-dlmMLE(rt,parm=rep(0,3),buildCAPM)  # rt return of indusrty 

mod<-buildCAPM(outMLE$par) 

outFilter<-dlmFilter(rt,mod) 

mae<-mean(abs(outFilter$f)-rt)   # MAE 

mse<-mean(((outFilter$f)-rt)^2) #MSE 

What I am asking how to modify this code as Kalman Filter Mean Reverting 

For example: 

R(it)= Alpha(it)+ Beta(it)R(mt)+ V(it) 

KF Mean Reverting 

Alpha(it)= Alphabar(i)+ phi* (Alpha(it-1)-Alphabar(i))+W(i1t) 
Beta(it)= Betabar(i)+ phi* (Beta(it-1)-Betahabar(i))+W(i2t) 

Please let me know if there is an any packages or codes  how to employ
Kalman Filter with Mean Reverting.

Regards, 
Serdar 



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