Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models

DOI10.1016/j.csda.2019.01.006OpenAlexW2964002469WikidataQ128591015 ScholiaQ128591015MaRDI QIDQ2416744

Colin S. Gillespie, Emma Bradley, Tom Lowe, Andrew Golightly

Publication date: 24 May 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1802.07148

zbMATH Keywords

Bayesian inferenceparticle MCMCchemical Langevin equationauxiliary particle filter (APF)Markov jump process (MJP)Poisson leap

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05)

Related Items

Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms ⋮ Accelerating Bayesian inference for stochastic epidemic models using incidence data ⋮ An improved approximate Bayesian computation scheme for parameter inference based on a recalibration post-processing method ⋮ Accelerating inference for stochastic kinetic models ⋮ Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods ⋮ Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes

Uses Software

• CODA

Cites Work

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