A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

DOI10.1007/s11222-015-9596-zzbMath1505.62284OpenAlexW1523626101WikidataQ62899374 ScholiaQ62899374MaRDI QIDQ340870

James M. McGree, Gentry White, Christopher C. Drovandi, Anthony N. Pettitt

Publication date: 15 November 2016

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://eprints.qut.edu.au/77732/4/77732.pdf

zbMATH Keywords

importance samplingparallel computingnonlinear regressionoptimal designLaplace approximationparticle filterintractable likelihoodgraphics processing unitrandomised quasi Monte Carlo

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Optimal statistical designs (62K05) Monte Carlo methods (65C05) Sequential statistical design (62L05) Numerical quadrature and cubature formulas (65D32)

Related Items

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data, Developments of the total entropy utility function for the dual purpose of model discrimination and parameter estimation in Bayesian design, A pseudo-marginal sequential Monte Carlo online smoothing algorithm, Bayesian sequential design for copula models, A Laplace-based algorithm for Bayesian adaptive design, Improving the efficiency of fully Bayesian optimal design of experiments using randomised quasi-Monte Carlo

Uses Software

• Matlab
• CUDA
• simannf90

Cites Work

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