Optimized auxiliary particle filters: adapting mixture proposals via convex optimization

Nicola Branchini, Víctor Elvira

Abstract: Auxiliary particle filters (APFs) are a class of sequential Monte Carlo (SMC) methods for Bayesian inference in state-space models. In their original derivation, APFs operate in an extended state s...