Archive for Bernoulli society
off to Lugano [EMS 2026]
Posted in Mountains, Statistics, Travel, University life with tags Bernoulli society, EMS 2026, European Meeting of Statisticians, Lago di Lugano, Lugano, Schweiz, Suisse, Svizzera, Università della Svizzera italiana on August 24, 2026 by xi'anEuropean Meeting of Statisticians, Lugano, 24-28 Aug 2026
Posted in Statistics with tags 35th European Meeting of Statisticians, Bernoulli society, Coventry, EMS 2026, EMS 2028, England, Lago di Lugano, Lugano, Switzerland, Ticino, Università della Svizzera italiana, University of Warwick on February 18, 2026 by xi'an
sampling using adaptive regenerative processes [in print!]
Posted in pictures, Statistics, University life with tags #ERCSyG, academic journals, adaptive MCMC methods, adaptive Monte Carlo algorithm, Bernoulli, Bernoulli society, eadem mutata resurgo, ERC Synergy Grant, Markov process, Ocean, Project euclid, regeneration, University of Warwick on November 16, 2024 by xi'an
important and published [Markov chains]
Posted in Books, Statistics, University life with tags Bernoulli society, CLT, geometric ergodicity, importance sampling, Law of Large Numbers, Markov kernel, MCMC, modes of a mixture, PhD students, residual sampling, semi-Markov chain, SPA, stochastic processes and their applications, vanilla Rao-Blackwellisation on February 26, 2024 by xi'an
Our importance Markov chain paper (with Charly Andral (PhD, Paris Dauphine), Randal Douc, and Hugo Marival (PhD, Telecom SudParis) has been published (on-line) by stochastic processes and their applications (SPA). Incidentally, my first publication in this journal. To paraphrase its abstract, it sort of bridges the (unsuspected?) gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), rather than the target of interest, the Importance Markov chain produces an extended Markov chain whose (first) marginal distribution converges to said target distribution. For instance, when targeting a multimodal distribution, the instrumental distribution can be chosen as a tempered version of the target and this frees the algorithm to explore its multiple modal regions more efficiently. We also derive a Law of Large Numbers and a Central Limit Theorem as well as prove geometric ergodicity for this extended kernel under mild assumptions on the instrumental kernel. Computationally, the algorithm is easy to implement and preexisting librairies can be used to sample from the instrumental distribution.
IMS Carver Award 2023
Posted in Books, pictures, Statistics, Travel, University life with tags Bernoulli society, IMS, IMS Carver Medal, Institute of Mathematical Statistics, Leif Döring, One World Bernoulli IMS conference on July 6, 2023 by xi'an
