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 --------------------------------- [[alternative HTML version deleted]]