Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation

24 October 2012

Papers citing "Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation"

12 / 12 papers shown

Title
Geometric Ergodicity in Modified Variations of Riemannian Manifold and Lagrangian Monte Carlo James A. Brofos Vivekananda Roy Roy R. Lederman 11 3 0 04 Jan 2023
A general perspective on the Metropolis-Hastings kernel Christophe Andrieu Anthony Lee Samuel Livingstone 15 24 0 29 Dec 2020
On parameter estimation with the Wasserstein distance Espen Bernton H. Shakespeare Mathieu Gerber Christian P. Robert 23 77 0 18 Jan 2017
Importance sampling type estimators based on approximate marginal MCMC M. Vihola Jouni Helske Jordan Franks 16 25 0 08 Sep 2016
Which ergodic averages have finite asymptotic variance? George Deligiannidis Anthony Lee 14 12 0 27 Jun 2016
On the Asymptotic Efficiency of Approximate Bayesian Computation Estimators Wentao Li Paul Fearnhead 36 62 0 10 Jun 2015
On a generalization of the preconditioned Crank-Nicolson Metropolis algorithm Daniel Rudolf Björn Sprungk 19 67 0 14 Apr 2015
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model M. Moores Geoff K. Nicholls A. Pettitt Kerrie Mengersen TPM 29 22 0 27 Mar 2015
Stability of Noisy Metropolis-Hastings F. Medina-Aguayo Anthony Lee Gareth O. Roberts 54 41 0 24 Mar 2015
Perfect simulation using atomic regeneration with application to Sequential Monte Carlo Anthony Lee Arnaud Doucet K. Latuszyñski 49 15 0 22 Jul 2014
Uniform ergodicity of the Particle Gibbs sampler Fredrik Lindsten Randal Douc Eric Moulines 49 54 0 03 Jan 2014
MCMC using Hamiltonian dynamics Radford M. Neal 176 3,260 0 09 Jun 2012