Direct fitting of dynamic models using integrated nested Laplace approximations — INLA

Inference in state-space models usually relies on recursive forms for filtering and smoothing of the state vectors regarding the temporal structure of the observations, an assumption that is, from our view point, unnecessary if the dataset is fixed, that is, completely available before analysis. In this paper, we propose a computational framework to perform approximate full Bayesian inference in linear and generalized dynamic linear models based...