Sequential Monte Carlo Sampling for State Space Models

24 Pages Posted: 25 Apr 2016

Date Written: April 25, 2016

Abstract

The aim of these notes is to revisit sequential Monte Carlo (SMC) sampling. SMC sampling is a powerful simulation tool for solving non-linear and/or non-Gaussian state space models. We illustrate this with several examples.

Keywords: State space models, sequential Monte Carlo sampling, SMC, Kalman filter

JEL Classification: C15, C22, C32

Suggested Citation

Wuthrich, Mario V., Sequential Monte Carlo Sampling for State Space Models (April 25, 2016). Available at SSRN: https://ssrn.com/abstract=2769748 or http://dx.doi.org/10.2139/ssrn.2769748

Mario V. Wuthrich (Contact Author)

RiskLab, ETH Zurich ( email )

Department of Mathematics
Ramistrasse 101
Zurich, 8092
Switzerland

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