I'm using the function
dlmGibbsDIG (Gibbs sampler) in the
dlmpackage from R to estimate the unknown variances. The output are the unknown variances together with the (saved) sampled states.
dlmFilter function performing the kalman filter only need as arguments the observations and the specified model (with the averaged variances gived by the output of
dlmGibbsDIG) but I'm confused about the role of the thetas (states) simulated by the Gibbs sampler above.