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Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation: Semi-automatic Approximate Bayesian Computation

P. Fearnhead, and D. Prangle. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 74 (3): 419--474 (June 2012)
DOI: 10.1111/j.1467-9868.2011.01010.x

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Heidi Paul-Toebelmann

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Motor unit number estimation via sequential Monte Carlo.S. Taylor, C. Sherlock, G. Ridall, and P. Fearnhead. Comput. Stat. Data Anal., (2020)Control variates for stochastic gradient MCMC.J. Baker, P. Fearnhead, E. Fox, and C. Nemeth. Stat. Comput., 29 (3): 599-615 (2019)Editorial: Special issue on adaptive Monte Carlo methods.P. Fearnhead. Stat. Comput., 18 (4): 341-342 (2008)Efficient computation of the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes.A. Chevallier, F. Cazals, and P. Fearnhead. CoRR, (2022)Subset Multivariate Collective and Point Anomaly Detection.A. Fisch, I. Eckley, and P. Fearnhead. J. Comput. Graph. Stat., 31 (1): 574-585 (January 2022)Spatial epidemiology and natural population structure of Campylobacter jejuni colonizing a farmland ecosystemN. French, M. Barrigas, P. Brown, P. Ribiero, N. Williams, H. Leatherbarrow, R. Birtles, E. Bolton, P. Fearnhead, and A. Fox. Environmental Microbiology, 7 (8): 1116--1126 (2005)Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data.T. Hocking, G. Rigaill, P. Fearnhead, and G. Bourque. J. Mach. Learn. Res., (2020)SequenceLDhot: detecting recombination hotspots.P. Fearnhead. Bioinform., 22 (24): 3061-3066 (2006)Computational methods for complex stochastic systems: a review of some alternatives to MCMC.P. Fearnhead. Stat. Comput., 18 (2): 151-171 (2008)Exact and efficient Bayesian inference for multiple changepoint problems.P. Fearnhead. Stat. Comput., 16 (2): 203-213 (2006)

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