Hi,

has anyone experience or an example how to setup a state space model for time varying regression coefficient estimates in R and how to get the filtered coefficient estimates.

The model looks like
                                        y(t) = a(t)'*x(t)+u(t)
where y(t) and x(t) are the observations at t=1,2,...,T. The coefficients a(t)'=(a_1(t),a_2(t),..,a_n(t)) follow a random walk
                                                    a_i(t)=a_i(t-1)+v_i(t).
The disturbances u(t) and v_i(t) are assumed to be normally distributed. 

Have found a finance example from Zivot using the SsfPack from S-Plus and have tried to get familiar with the sspir and the dse package from R but I have problems to adapt the examples in those packages.

Thanks for your help.

Regards,
Daphne


       
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