A practical guide to pseudo-marginal methods for computational inference in systems biology

28 December 2019

Papers citing "A practical guide to pseudo-marginal methods for computational inference in systems biology"

12 / 12 papers shown

Title
Particle Methods for Stochastic Differential Equation Mixed Effects Models Imke Botha Robert Kohn Christopher C. Drovandi 27 21 0 25 Jul 2019
Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem Mathieu Besançon Theodore Papamarkou D. Anthoff Alex Arslan Simon Byrne Dahua Lin John Pearson GP 52 80 0 19 Jul 2019
Efficient Bayesian estimation for GARCH-type models via Sequential Monte Carlo Dan Li A. Clements Christopher C. Drovandi 33 16 0 10 Jun 2019
$Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC$ Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC Aki Vehtari Andrew Gelman Daniel P. Simpson Bob Carpenter Paul-Christian Bürkner 32 919 0 19 Mar 2019
Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo Ajay Jasra K. Kamatani K. Law Yan Zhou 32 30 0 20 Jan 2017
Approximation and inference methods for stochastic biochemical kinetics - a tutorial review David Schnoerr G. Sanguinetti R. Grima 112 217 0 23 Aug 2016
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 67 232 0 11 Jul 2016
Multilevel particle filter Ajay Jasra K. Kamatani K. Law Yan Zhou 55 72 0 16 Oct 2015
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster S. Cotter Gareth O. Roberts Andrew M. Stuart D. White 62 480 0 03 Feb 2012
The pseudo-marginal approach for efficient Monte Carlo computations Christophe Andrieu Gareth O. Roberts 112 890 0 31 Mar 2009
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Tina Toni David Welch N. Strelkowa Andreas Ipsen M. Stumpf 155 1,542 0 14 Jan 2009
Approximate Bayesian computation (ABC) gives exact results under the assumption of model error Richard D. Wilkinson 77 273 0 20 Nov 2008