oaioai:HAL:inria-00403917v1

Particle methods: An introduction with applications

Abstract

Interacting particle methods are increasingly used to sample from complex high-dimensional distributions. They have found a wide range of applications in applied probability, Bayesian statistics and information engineering. Understanding rigorously these new Monte Carlo simulation tools leads to fascinating mathematics related to Feynman-Kac path integral theory and their interacting particle interpretations. In these lecture notes, we provide a pedagogical introduction to the stochastic modeling and the theoretical analysis of these particle algorithms. We also illustrate these methods through several applications including random walk confinements, particle absorption models, nonlinear filtering, stochastic optimization, combinatorial counting and directed polymer models

Similar works

Full text

thumbnail-image

INRIA a CCSD electronic archive server

Provided a free PDF
oaioai:HAL:inria-00403917v1Last time updated on 11/9/2016View original full text link

This paper was published in INRIA a CCSD electronic archive server.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.