Publications by xi'an
delayed in Seattle
Here are the slides of my talk on delayed acceptance I present this afternoon at JSM 2015, in Seattle, in the Bayesian Computation I (2pm, room CC-4C1) and II (4pm, room CC-3A) sessions Omiros Papaspiliopoulos and myself put together (sponsored by IMS and ISBA): Filed under: Books, R, Statistics, Travel, University life Tagged: American Statistic...
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JSM 2015 [day #1]
This afternoon, at JSM 2015, in Seattle, we had the Bayesian Computation I and II sessions that Omiros Papaspiliopoulos and myself put together (sponsored by IMS and ISBA). Despite this being Sunday and hence having some of the participants still arriving, the sessions went on well in terms of audience. Thanks to Mark Girolami’s strict presiden...
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JSM 2015 [day #2]
Today, at JSM 2015, in Seattle, I attended several Bayesian sessions, having sadly missed the Dennis Lindley memorial session yesterday, as it clashed with my own session. In the morning sessions on Bayesian model choice, David Rossell (Warwick) defended non-local priors à la Johnson (& Rossell) as having better frequentist properties. Although ...
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STAN trailer [PG+53]
[Heading off to mountainous areas with no Internet or phone connection, I posted a series of entries for the following week, starting with this brilliant trailer of Michael:] Filed under: Kids, R, Statistics, University life Tagged: Andrew Gelman, Hamiltonian Monte Carlo, STAN, statistical software, trailer Related To leave a comment for the ...
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Seattle histogram
Filed under: pictures, R, Statistics, Travel Tagged: histogram, sculpture, Seattle, Washington Convention Center Related To leave a comment for the author, please follow the link and comment on their blog: Xi'an's Og » R. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click her...
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abcfr 0.9-3
In conjunction with our reliable ABC model choice via random forest paper, about to be resubmitted to Bioinformatics, we have contributed an R package called abcrf that produces a most likely model and its posterior probability out of an ABC reference table. In conjunction with the realisation that we could devise an approximation to the (ABC) po...
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likelihood-free inference in high-dimensional models
“…for a general linear model (GLM), a single linear function is a sufficient statistic for each associated parameter…” The recently arXived paper “Likelihood-free inference in high-dimensional models“, by Kousathanas et al. (July 2015), proposes an ABC resolution of the dimensionality curse [when the dimension of the parameter and of ...
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reaching transcendence for Gaussian mixtures
“…likelihood inference is in a fundamental way more complicated than the classical method of moments.” Carlos Amendola, Mathias Drton, and Bernd Sturmfels arXived a paper this Friday on “maximum likelihood estimates for Gaussian mixtures are transcendental”. By which they mean that trying to solve the five likelihood equations for a tw...
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ABC model choice via random forests [and no fire]
While my arXiv newspage today had a puzzling entry about modelling UFOs sightings in France, it also broadcast our revision of Reliable ABC model choice via random forests, version that we resubmitted today to Bioinformatics after a quite thorough upgrade, the most dramatic one being the realisation we could also approximate the posterior probabi...
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debunking a (minor and personal) myth
For quite a while, I entertained the idea that Beta and Dirichlet proposals were more adequate than (log-)normal random walks proposals for parameters on (0,1) and simplicia (simplices, simplexes), respectively, when running an MCMC. For instance, for p in (0,1) the value of the Markov chain at time t-1, the proposal at time t could be a Be(εp...
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