We consider the generic problem of performing sequential Bayesian inference
in a state-space model with observation process $(y_{t})$, state process
$(x_{t})$ and fixed parameter $\theta$. An idealized approach would be to apply
the \emph{iterated batch importance sampling} (IBIS) algorithm of
\citet{Chopin:IBIS}. This is a sequential Monte Carlo algorithm \emph{in the