In connection with our ABC-PMC paper, to appear in Biometrika, the authors of the original ABC-PRC paper have recently published a corrigendum in PNAS that agrees with our analysis of the bias., due to the likelihood ratio approximation based on two unbiased estimators being itself biased. The correction they propose is to modify the denominator […]

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## ABC-PRC: Correction posted on PNAS

September 4, 2009## Is ABC-PRC truly PRC?

January 9, 2009When re-reading the supplementary material in the Appendix of Sisson et al. (2007b) yesterday, I found I have an additional difficulty with the ABC-PRC algorithm that is related with the partial rejection control (PRC) perspective. Indeed, the PRC idea as described in Jun Liu’s 2001 book is to resample from a population of weighted particles […]

## adaptive ABC tolerance

June 2, 2020“There are three common approaches for selecting the tolerance sequence (…) [they] can lead to inefficient sampling” Umberto Simola, Jessi Cisewski-Kehe, Michael Gutmann and Jukka Corander recently arXived a paper entitled Adaptive Approximate Bayesian Computation Tolerance Selection. I appreciate that they start from our ABC-PMC paper, i.e., Beaumont et al. (2009) [although the representation that […]

## Another ABC paper

July 24, 2010“One aim is to extend the approach of Sisson et al. (2007) to provide an algorithm that is robust to implement.” C.C. Drovandi & A.N. Pettitt A paper by Drovandi and Pettit appeared in the Early View section of Biometrics. It uses a combination of particles and of MCMC moves to adapt to the true […]

## Inference in epidemic models w/o likelihoods

July 21, 2010“We discuss situations in which we think simulation-based inference may be preferable to likelihood-based inference.” McKinley, Cook, and Deardon, IJB I only became aware last week of the paper Inference in epidemic models without likelihoods by McKinley, Cook and Deardon, published in the International Journal of Biostatistics in 2009. (Anyone can access the paper by […]