## Sequential Monte Carlo Samplers (2002)

Citations: | 141 - 24 self |

### BibTeX

@MISC{Moral02sequentialmonte,

author = {Pierre Del Moral and Arnaud Doucet and Toulouse France},

title = {Sequential Monte Carlo Samplers},

year = {2002}

}

### Years of Citing Articles

### OpenURL

### Abstract

In this paper, we propose a general algorithm to sample sequentially from a sequence of probability distributions known up to a normalizing constant and de ned on a common space. A sequence of increasingly large arti cial joint distributions is built; each of these distributions admits a marginal which is a distribution of interest. To sample from these distributions, we use sequential Monte Carlo methods. We show that these methods can be interpreted as interacting particle approximations of a nonlinear Feynman-Kac ow in distribution space. One interpretation of the Feynman-Kac ow corresponds to a nonlinear Markov kernel admitting a speci ed invariant distribution and is a natural nonlinear extension of the standard Metropolis-Hastings algorithm. Many theoretical results have already been established for such ows and their particle approximations. We demonstrate the use of these algorithms through simulation.