Archive for University of Reading

afternoon on Bayesian computation

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , , on April 6, 2016 by xi'an

Richard Everitt organises an afternoon workshop on Bayesian computation in Reading, UK, on April 19, the day before the Estimating Constant workshop in Warwick, following a successful afternoon last year. Here is the programme:

1230-1315  Antonietta Mira, Università della Svizzera italiana
1315-1345  Ingmar Schuster, Université Paris-Dauphine
1345-1415  Francois-Xavier Briol, University of Warwick
1415-1445  Jack Baker, University of Lancaster
1445-1515  Alexander Mihailov, University of Reading
1515-1545  Coffee break
1545-1630  Arnaud Doucet, University of Oxford
1630-1700  Philip Maybank, University of Reading
1700-1730  Elske van der Vaart, University of Reading
1730-1800  Reham Badawy, Aston University
1815-late  Pub and food (SCR, UoR campus)

and the general abstract:

The Bayesian approach to statistical inference has seen major successes in the past twenty years, finding application in many areas of science, engineering, finance and elsewhere. The main drivers of these successes were developments in Monte Carlo methods and the wide availability of desktop computers. More recently, the use of standard Monte Carlo methods has become infeasible due the size and complexity of data now available. This has been countered by the development of next-generation Monte Carlo techniques, which are the topic of this meeting.

The meeting takes place in the Nike Lecture Theatre, Agriculture Building [building number 59].

postdoc on Bayesian computation for statistical genomics

Posted in Kids, Statistics, Travel, University life with tags , , , , , on February 24, 2016 by xi'an

[An opportunity to work with Richard Everitt in Reading, UK, in a postdoc position starting this summer]

It is now possible to retrieve the complete DNA sequence of a bacterial strain relatively quickly and cheaply, and population genetics has been revolutionised in the past ten years through the availability of these data. To gain a deep understanding of sequence data, model-based statistical techniques are required. However, current approaches for performing inference in these models do not scale to whole genome sequence data. The BBSRC project “Understanding recombination through tractable statistical analysis of whole genome sequences” aims to address this issue. A position as Post-Doctoral Research Assistant is available on this project, supervised by Dr Richard Everitt in the Statistics group at the Department of Mathematics & Statistics at the University of Reading.

The deadline for applications is March 31, 2016 (details).

Robert’s paradox [reading in Reading]

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , on January 28, 2015 by xi'an

paradoxOn Wednesday afternoon, Richard Everitt and Dennis Prangle organised an RSS workshop in Reading on Bayesian Computation. And invited me to give a talk there, along with John Hemmings, Christophe Andrieu, Marcelo Pereyra, and themselves. Given the proximity between Oxford and Reading, this felt like a neighbourly visit, especially when I realised I could take my bike on the train! John Hemmings gave a presentation on synthetic models for climate change and their evaluation, which could have some connection with Tony O’Hagan’s recent talk in Warwick, Dennis told us about “the lazier ABC” version in connection with his “lazy ABC” paper, [from my very personal view] Marcelo expanded on the Moreau-Yoshida expansion he had presented in Bristol about six months ago, with the notion that using a Gaussian tail regularisation of a super-Gaussian target in a Langevin algorithm could produce better convergence guarantees than the competition, including Hamiltonian Monte Carlo, Luke Kelly spoke about an extension of phylogenetic trees using a notion of lateral transfer, and Richard introduced a notion of biased approximation to Metropolis-Hasting acceptance ratios, notion that I found quite attractive if not completely formalised, as there should be a Monte Carlo equivalent to the improvement brought by biased Bayes estimators over unbiased classical counterparts. (Repeating a remark by Persi Diaconis made more than 20 years ago.) Christophe Andrieu also exposed some recent developments of his on exact approximations à la Andrieu and Roberts (2009).

Since those developments are not yet finalised into an archived document, I will not delve into the details, but I found the results quite impressive and worth exploring, so I am looking forward to the incoming publication. One aspect of the talk which I can comment on is related to the exchange algorithm of Murray et al. (2006). Let me recall that this algorithm handles double intractable problems (i.e., likelihoods with intractable normalising constants like the Ising model), by introducing auxiliary variables with the same distribution as the data given the new value of the parameter and computing an augmented acceptance ratio which expectation is the targeted acceptance ratio and which conveniently removes the unknown normalising constants. This auxiliary scheme produces a random acceptance ratio and hence differs from the exact-approximation MCMC approach, which target directly the intractable likelihood. It somewhat replaces the unknown constant with the density taken at a plausible realisation, hence providing a proper scale. At least for the new value. I wonder if a comparison has been conducted between both versions, the naïve intuition being that the ratio of estimates should be more variable than the estimate of the ratio. More generally, it seemed to me [during the introductory part of Christophe’s talk] that those different methods always faced a harmonic mean danger when being phrased as expectations of ratios, since those ratios were not necessarily squared integrable. And not necessarily bounded. Hence my rather gratuitous suggestion of using other tools than the expectation, like maybe a median, thus circling back to the biased estimators of Richard. (And later cycling back, unscathed, to Reading station!)

On top of the six talks in the afternoon, there was a small poster session during the tea break, where I met Garth Holloway, working in agricultural economics, who happened to be a (unsuspected) fan of mine!, to the point of entitling his poster “Robert’s paradox”!!! The problem covered by this undeserved denomination connected to the bias in Chib’s approximation of the evidence in mixture estimation, a phenomenon that I related to the exchangeability of the component parameters in an earlier paper or set of slides. So “my” paradox is essentially label (un)switching and its consequences. For which I cannot claim any fame! Still, I am looking forward the completed version of this poster to discuss Garth’s solution, but we had a beer together after the talks, drinking to the health of our mutual friend John Deely.