Archive for the Mountains Category

at the centre of Bayes

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , on October 14, 2019 by xi'an

Japanese mushrooms [jatp]

Posted in Mountains, pictures, Running, Travel with tags , , , , , , , on October 12, 2019 by xi'an

Antarctic sabbatical

Posted in Mountains, Travel, University life with tags , , , , , on September 29, 2019 by xi'an

Airbnb is supporting 5 volunteers that wish to join next December environmental scientist Kirstie Jones-Williams, from the University of Exeter, on a scientific expedition in Antarctica, investigating the presence of microplastics there. The deadline for applications  is 11:59pm EDT on 8 October 2019. (I wish I could, but the news came a bit late to contemplate rescheduling a large number of classes.) As the offer includes riding snowmobiles and fat tyre bikes, and visiting sites over Antarctica, during the one week stay there, this obviously sounds more like covert tourism than a genuine expedition. With a dose of greenwashing by Airbnb, “inherently more eco-friendly than other forms of travel given that people are using spaces already built” to quote from the University of Exeter webpage, which does not mention the impact of airbnbing locals out of city centres by drying out long-term rentals and raising housing prices sky-high… (As a long-term user of airbnb, hence accomplice to the fact, I noticed a rising proportion of places that are sheer around-the-year rentals rather than occasionally let to visitors. And hope the alternative platform fairbnb.coop will launch soon.)

ABC in Clermont-Ferrand

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on September 20, 2019 by xi'an

Today I am taking part in a one-day workshop at the Université of Clermont Auvergne on ABC. With applications to cosmostatistics, along with Martin Kilbinger [with whom I worked on PMC schemes], Florent Leclerc and Grégoire Aufort. This should prove a most exciting day! (With not enough time to run up Puy de Dôme in the morning, though.)

two positions at UBC

Posted in Mountains, pictures, Travel, University life with tags , , , , , , , , , , on September 15, 2019 by xi'an

A long-time friend at UBC pointed out to me the opening of two tenure-track Assistant Professor positions at the Department of Statistics at the University of British Columbia, Vancouver, with an anticipated start date of July 1, 2020 or January 1, 2021. The deadline for applications is October 18, 2019. Statistics at UBC is an internationally renowned department, in particular (but not restricted to) computational statistics and Bayesian methods and this is a great opportunity to join this department. (Not mentioning the unique location of the campus and the beautiful surroundings of the city of Vancouver!)

Salzburg castle [jatp]

Posted in Mountains, pictures, Travel with tags , , , , , , on September 9, 2019 by xi'an

likelihood-free inference by ratio estimation

Posted in Books, Mountains, pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , on September 9, 2019 by xi'an

“This approach for posterior estimation with generative models mirrors the approach of Gutmann and Hyvärinen (2012) for the estimation of unnormalised models. The main difference is that here we classify between two simulated data sets while Gutmann and Hyvärinen (2012) classified between the observed data and simulated reference data.”

A 2018 arXiv posting by Owen Thomas et al. (including my colleague at Warwick, Rito Dutta, CoI warning!) about estimating the likelihood (and the posterior) when it is intractable. Likelihood-free but not ABC, since the ratio likelihood to marginal is estimated in a non- or semi-parametric (and biased) way. Following Geyer’s 1994 fabulous estimate of an unknown normalising constant via logistic regression, the current paper which I read in preparation for my discussion in the ABC optimal design in Salzburg uses probabilistic classification and an exponential family representation of the ratio. Opposing data from the density and data from the marginal, assuming both can be readily produced. The logistic regression minimizing the asymptotic classification error is the logistic transform of the log-ratio. For a finite (double) sample, this minimization thus leads to an empirical version of the ratio. Or to a smooth version if the log-ratio is represented as a convex combination of summary statistics, turning the approximation into an exponential family,  which is a clever way to buckle the buckle towards ABC notions. And synthetic likelihood. Although with a difference in estimating the exponential family parameters β(θ) by minimizing the classification error, parameters that are indeed conditional on the parameter θ. Actually the paper introduces a further penalisation or regularisation term on those parameters β(θ), which could have been processed by Bayesian Lasso instead. This step is essentially dirving the selection of the summaries, except that it is for each value of the parameter θ, at the expense of a X-validation step. This is quite an original approach, as far as I can tell, but I wonder at the link with more standard density estimation methods, in particular in terms of the precision of the resulting estimate (and the speed of convergence with the sample size, if convergence there is).