A sharp first order analysis of Feynman-Kac particle models. II: Particle Gibbs samplers

DOI10.1016/J.SPA.2017.05.001zbMath1392.60077OpenAlexW2612334188MaRDI QIDQ1683822

Ajay Jasra, Pierre Del Moral

Publication date: 1 December 2017

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spa.2017.05.001

zbMATH Keywords

propagation of chaosparticle simulationmean field particle modelsFeynman-Kac formulaecontraction inequalitiesDobrushin coefficientsminorization conditionsparticle Gibbs samplers

Mathematics Subject Classification ID

Point estimation (62F10) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Feynman integrals and graphs; applications of algebraic topology and algebraic geometry (81Q30)

Related Items (1)

A duality formula and a particle Gibbs sampler for continuous time Feynman-Kac measures on path spaces

Cites Work

• Unnamed Item
• On particle Gibbs samplers
• A nonasymptotic theorem for unnormalized Feynman-Kac particle models
• A duality formula for Feynman-Kac path particle models
• Inference in hidden Markov models.
• Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers
• On particle Gibbs sampling
• Sequential Monte Carlo Methods in Practice
• Mean Field Simulation for Monte Carlo Integration
• Uniform Ergodicity of the Particle Gibbs Sampler
• Particle Markov Chain Monte Carlo Methods

This page was built for publication: A sharp first order analysis of Feynman-Kac particle models. II: Particle Gibbs samplers