Robust inference on parameters via particle filters and sandwich covariance matrices - Shephard, N; Doucet, A (University of Oxford, 2012)
Likelihood based estimation of the parameters of state space models can be carried out via a particle filter. In this paper we show how to make valid inference on such parameters when the model is incorrect. In particular we develop a simulation strategy for computing sandwich covariance matrices which can be used for asymptotic likelihood based inference. These methods are illustrated on some simulated data.