I am a professor of Statistics at Universit Paris Dauphine, with two teenage kids who are taking a lot of my free time, a definitely unhealthy but so far not fatal) fascination for mountains and (easy) climbing, in particular for Scotland in Winter, an almost-daily run, and a reading list mainly centered at fantasy books? Hence the categories on this blog (or 'og, because 'log and b'og did not sound good). The Statistics posts will be mainly centered on computational and Bayesian topics, on papers or preprints I find of interest (or worth criticising), and on the occasional trip abroad to a research center or to a conference.
Xi'an's Og's Latest Posts
Mark Huber just arXived a short paper where he develops a Monte Carlo approach that bounds the probability of large errors by computing a lower bound on the sample size r and I wondered at the presence of μ in the bound as it indicates the approach is not translation invariant. One reason is that […]
Among the many comments (thanks!) I received when posting our Testing via mixture estimation paper came the suggestion to relate this approach to the notion of full Bayesian significance test (FBST) developed by (Julio, not Hal) Stern and Pereira, from São Paulo, Brazil. I thus had a look at this alternative and read the Bayesian […]
Michael Stumpf sent me Topological sensitivity analysis for systems biology, written by Ann Babtie and Paul Kirk, en avant-première before it came out in PNAS and I read it during the trip to NIPS in Montréal. (The paper is published in open access, so everyone can read it now!) The topic is quite central to a […]
Filed under: pictures, Travel Tagged: Canada, Montréal, NIPS, Québec, snow, street view
I was reading [in the Paris métro] Hastings-Metropolis algorithm on Markov chains for small-probability estimation, arXived a few weeks ago by François Bachoc, Lionel Lenôtre, and Achref Bachouch, when I came upon their first algorithm that reminded me much of nested sampling: the following was proposed by Guyader et al. in 2011, To approximate a […]
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