In a 2009 JCGS paper, Peter Lenk proposed a bias correction of the harmonic mean estimator, which is somewhat surprising given that the estimator usually has no variance and hence that its consistency is purely formal, since no speed of convergence can be taken for granted. In particular, the conjugate Normal model serving as a […]
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back to a correction of the harmonic mean estimator
May 11, 2023Another harmonic mean
May 21, 2022Yet another paper that addresses the approximation of the marginal likelihood by a truncated harmonic mean, a popular theme of mine. A 2020 paper by Johannes Reich, entitled Estimating marginal likelihoods from the posterior draws through a geometric identity and published in Monte Carlo Methods and Applications. The geometric identity it aims at exploiting is […]
machine-learning harmonic mean
February 25, 2022In a recent arXival, Jason McEwen propose a resurrection of the “infamous” harmonic mean estimator. In Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator, they propose to aim at the “optimal importance function”. The paper provides a fair coverage of the literature on that topic, incl. our 2009 paper with Darren Wraith (although […]
a come-back of the harmonic mean estimator
September 6, 2018Are we in for a return of the harmonic mean estimator?! Allen Caldwell and co-authors arXived a new document that Allen also sent me, following a technique that offers similarities with our earlier approach with Darren Wraith, the difference being in the more careful and practical construct of the partition set and use of multiple […]
another version of the corrected harmonic mean estimator
June 11, 2018A few days ago I came across a short paper in the Central European Journal of Economic Modelling and Econometrics by Pajor and Osiewalski that proposes a correction to the infamous harmonic mean estimator that is essentially the one Darren and I made in 2009, namely to restrict the evaluations of the likelihood function to […]