the kingfisher and the heron [jatp]

flotsam [art brut]

Drake Island beach (#2)

Drake Island beach (#1)

do and [mostly] don’t…

Rather than staying in one of the conference hotels, I followed my habit of renting a flat by finding a nice studio in Cancún via airbnb. Fine except for having no internet connection. (The rental description mentioned “Wifi in the lobby”, which I stupidly interpreted as “lobby of the appartment”, but actually meant “lobby of the condominium building”… Could as well have been “lobby of the airport”.) The condo owner sent us a list of “don’t” a few days ago, some of which are just plain funny (or tell of past disasters!):

– don’t drink heavily
– don’t party or make noise
– don’t host visitors, day or night
– don’t bang the front door or leave the balcony door open when opening the front door
– don’t put cans or bottles on top of the glass cooktop
– don’t cook elaborate meals
– don’t try to fit an entire chicken in the oven
– don’t spill oil or wine on the kitchentop
– don’t cut food directly on the kitchentop
– don’t eat or drink while in bed
– avoid frying, curry, and bacon
– shop for groceries only one day at a time
– hot water may or may not be available
– elevator may or may not be available
– don’t bring sand back in the condo

Cancun, ISBA 2014 [½ day #2]

Half-day #2 indeed at ISBA 2014, as the Wednesday afternoon kept to the Valencia tradition of free time, and potential cultural excursions, so there were only talks in the morning. And still the core poster session at (late) night. In which my student Kaniav Kamari presented a poster on a current project we are running with Kerrie Mengersen and Judith Rousseau on the replacement of the standard Bayesian testing setting with a mixture representation. Being half-asleep by the time the session started, I did not stay long enough to collect data on the reactions to this proposal, but the paper should be arXived pretty soon. And Kate Lee gave a poster on our importance sampler for evidence approximation in mixtures (soon to be revised!). There was also an interesting poster about reparameterisation towards higher efficiency of MCMC algorithms, intersecting with my long-going interest in the matter, although I cannot find a mention of it in the abstracts. And I had a nice talk with Eduardo Gutierrez-Pena about infering on credible intervals through loss functions. There were also a couple of appealing posters on g-priors. Except I was sleepwalking by the time I spotted them… (My conference sleeping pattern does not work that well for ISBA meetings! Thankfully, both next editions will be in Europe.)

Great talk by Steve McEachern that linked to our ABC work on Bayesian model choice with insufficient statistics, arguing towards robustification of Bayesian inference by only using summary statistics. Despite this being “against the hubris of Bayes”… Obviously, the talk just gave a flavour of Steve’s perspective on that topic and I hope I can read more to see how we agree (or not!) on this notion of using insufficient summaries to conduct inference rather than trying to model “the whole world”, given the mistrust we must preserve about models and likelihoods. And another great talk by Ioanna Manolopoulou on another of my pet topics, capture-recapture, although she phrased it as a partly identified model (as in Kline’s talk yesterday). This related with capture-recapture in that when estimating a capture-recapture model with covariates, sampling and inference are biased as well. I appreciated particularly the use of BART to analyse the bias in the modelling. And the talk provided a nice counterpoint to the rather pessimistic approach of Kline’s.

Terrific plenary sessions as well, from Wilke’s spatio-temporal models (in the spirit of his superb book with Noel Cressie) to Igor Prunster’s great entry on Gibbs process priors. With the highly significant conclusion that those processes are best suited for (in the sense that they are only consistent for) discrete support distributions. Alternatives are to be used for continuous support distributions, the special case of a Dirichlet prior constituting a sort of unique counter-example. Quite an inspiring talk (even though I had a few micro-naps throughout it!).

I shared my afternoon free time between discussing the next O’Bayes meeting (2015 is getting very close!) with friends from the Objective Bayes section, getting a quick look at the Museo Maya de Cancún (terrific building!), and getting some work done (thanks to the lack of wireless…)

an easy pun on conditional risk[cd]