I am using
diffuse_filter in estimation.
After estimation I did these two procedures independent.
I got predictive density using forecasts saved across draws in the metropolis-subfolder in the FILENAME_forc_point*.mat-files. It looks good.
When I retrieve a space-state representation using output after estimation,
M_.Sigma_eand I forecast the state-space model using Monte-Carlo method the density predictive is some explosive. In this forecast I am using ssm function of matlab which use standard Kalman filter (“no diffuse”) to get the initial state means and covariances. So I suspect the explosiveness is dued to using standard filter.
My question is: ¿should I use diffuse filter to compute the initial state means and covariances to initialize forecast (and respectively, should I use diffuse filter to compute forward recursions too)?
Thanks a lot.