## Archive for England

## snapshot from Oxford [#2]

Posted in Kids, pictures, Travel, University life with tags England, lawn, Magdalen College, University of Oxford, winter light on February 9, 2016 by xi'an## Oxford snapshot

Posted in pictures, Running, Travel, University life with tags England, Oxford, St. Edmund Hall, University of Oxford on February 2, 2016 by xi'an## read paper [in Bristol]

Posted in Books, pictures, Statistics, Travel, University life with tags Bayes factors, Bayesian hypothesis testing, Bayesian model choice, Bristol, cake, England, improper priors, mixtures of distributions, Neyman-Pearson, non-informative priors, parametrisation, Pima Indians, Read paper, seminar, University of Bristol on January 29, 2016 by xi'an**I** went to give a seminar in Bristol last Friday and I chose to present the testing with mixture paper. As we are busy working on the revision, I was eagerly looking for comments and criticisms that could strengthen this new version. As it happened, the (Bristol) Bayesian Cake (Reading) Club had chosen our paper for discussion, two weeks in a row!, hence the title!, and I got invited to join the group the morning prior to the seminar! This was, of course, most enjoyable and relaxed, including an home-made cake!, but also quite helpful in assessing our arguments in the paper. One point of contention or at least of discussion was the common parametrisation between the components of the mixture. Although all parametrisations are equivalent from a *single* component point of view, I can [almost] see why using a mixture with the same parameter value on all components may impose some unsuspected constraint on that parameter. Even when the parameter is *the same moment* for both components. This still sounds like a minor counterpoint in that the weight should converge to either zero or one and hence eventually favour the posterior on the parameter corresponding to the “true” model.

Another point that was raised during the discussion is the behaviour of the method under misspecification or for an M-open framework: when neither model is correct does the weight still converge to the boundary associated with the closest model (as I believe) or does a convexity argument produce a non-zero weight as it limit (as hinted by one example in the paper)? I had thought very little about this and hence had just as little to argue though as this does not sound to me like the primary reason for conducting tests. Especially in a Bayesian framework. If one is uncertain about both models to be compared, one should have an alternative at the ready! Or use a non-parametric version, which is a direction we need to explore deeper before deciding it is coherent and convergent!

A third point of discussion was my argument that mixtures allow us to rely on the same parameter and hence the same prior, whether proper or not, while Bayes factors are less clearly open to this interpretation. This was not uniformly accepted!

Thinking afresh about this approach also led me to broaden my perspective on the use of the posterior distribution of the weight(s) α: while previously I had taken those weights mostly as a proxy to the posterior probabilities, to be calibrated by pseudo-data experiments, as for instance in Figure 9, I now perceive them primarily as the portion of the data in agreement with the corresponding model [or hypothesis] and more importantly as a solution for staying away from a Neyman-Pearson-like decision. Or error evaluation. Usually, when asked about the interpretation of the output, my answer is to compare the behaviour of the posterior on the weight(s) with a posterior associated with a sample from each model. Which does sound somewhat similar to posterior predictives if the samples are simulated from the associated predictives. But the issue was not raised during the visit to Bristol, which possibly reflects on how unfrequentist the audience was [the Statistics group is], as it apparently accepted with no further ado the use of a posterior distribution as a soft assessment of the comparative fits of the different models. If not necessarily agreeing the need of conducting hypothesis testing (especially in the case of the Pima Indian dataset!).

## animal picture of the year

Posted in Kids, pictures with tags England, London, weasel, wildlife photography, woodpecker on December 31, 2015 by xi'an## delayed & robbed in London [CFE-CMStatistics 2015]

Posted in Kids, pictures, Statistics, Travel, University life, Wines with tags ABC, bike, Birbeck College, CFE 2015, CMStatistics 2015, delayed acceptance, econometrics, Elsevier, England, ERCIM, Gower Street, London, stolen bike, UCL, Waterstones on December 26, 2015 by xi'an**L**ast Sunday, I gave a talk on delayed acceptance at the 9th International Conference on Computational and Financial Econometrics (CFE 2015), joint with CMStatistics 2015, in London. This was a worthwhile session, with other talks by Matias Quiroz, on subsampling strategies for large data, David Frazier, on our joint paper about the consistency of ABC algorithms, and James Ridgway not on Pima Indians! And with a good-sized audience especially when considering the number of parallel sessions (36!). Earlier that day, I also attended an equally interesting session on the calibration of misspecified Bayesian models including talks by Peter Green [with a potential answer to the difficulty of parameters on the boundaries by adding orthogonal priors on those boundaries] and Julien Stoehr. calibrating composite likelihoods on Gaussian random fields. In the evening I went to a pub I had last visited when my late friend Costas Goutis was still at UCL and later enjoyed a fiery hot rogan josh.

While I could have attended two more sessions the next morning, I took advantage of the nice café in the Gower Street Waterstones to work a few hours with co-authors (and drink a few litres of tea from real teapots). Despite this quite nice overall experience, the 36 parallel session and the 1600 plus attendants at the conference still make wonder at the appeal of such a large conference and at the pertinence of giving a talk in parallel with so many other talks. And on about all aspects of statistics and econometrics. One JSM (or one NIPS) is more than enough! And given that many people only came for delivering their talk, there is very little networking between research teams or mentoring of younger colleagues, as far as I can tell. And no connection with a statistical society (it would be so nice if the RSS annual conference could only attract 1600 people!). Only a “CMStatistics working group” of which I discovered I was listed as a member [and asked for removal, so far with no answer]. Whose goals and actions are unclear, except to support Elsevier journals with special issues apparently constructed on the same pattern as this conference was organised, i.e., by asking people to take care [for free!] of gathering authors on a theme of their choice. And behind this “working group” an equally nebulous structure called ERCIM…

While the “robbed” in the title could be interpreted as wondering at the reason for paying such high registration fees (£250 for very early birds), I actually got robbed of my bicycle while away at the conference. Second bike stolen within a calendar year, quite an achievement! This was an old 1990 mountain bike I had bought in Cornell and carried back to France, in such a poor state that I could not imagine anyone stealing it. Wrong prior, obviously.