Archive for the University life Category

fiducial simulation

Posted in Books, Kids, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on April 19, 2018 by xi'an

While reading Confidence, Likelihood, Probability), by Tore Schweder and Nils Hjort, in the train from Oxford to Warwick, I came upon this unexpected property shown by Lindqvist and Taraldsen (Biometrika, 2005) that to simulate a sample y conditional on the realisation of a sufficient statistic, T(y)=t⁰, it is sufficient (!!!) to simulate the components of  y as y=G(u,θ), with u a random variable with fixed distribution, e.g., a U(0,1), and to solve in θ the fixed point equation T(y)=t⁰. Assuming there exists a single solution. Brilliant (like an aurora borealis)! To borrow a simple example from the authors, take an exponential sample to be simulated given the sum statistics. As it is well-known, the conditional distribution is then a (rescaled) Beta and the proposed algorithm ends up being a standard Beta generator. For the method to work in general, T(y) must factorise through a function of the u’s, a so-called pivotal condition which brings us back to my post title. If this condition does not hold, the authors once again brilliantly introduce a pseudo-prior distribution on the parameter θ to make it independent from the u’s conditional on T(y)=t⁰. And discuss the choice of the Jeffreys prior as optimal in this setting even when this prior is improper. While the setting is necessarily one of exponential families and of sufficient conditioning statistics, I find it amazing that this property is not more well-known [at least by me!]. And wonder if there is an equivalent outside exponential families, for instance for simulating a t sample conditional on the average of this sample.

guess what..?! Yet another worskhop in the endless summer Bayesian series!

Posted in Mountains, pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , on April 18, 2018 by xi'an

Dennis Prangle pointed to me the perfectly timed i-like workshop taking place in Newcastle, on the days priors to ABC in Edinburgh and ISBA (similarly in Edinburgh!). (Note that Warwick is also part of the i-like network. Actually, the first i-like workshop was my first trip abroad after the Accident!) I may sound negative about these workshops, but on the opposite am quite a fan of them, just regretting that the main event did not take advantage of them all to reduce the volume of talks there. As I suggested, it could have been feasible to label these satellites as part of the main conference towards making speakers at these officially speakers at ISBA 2018 in case talks were required for support…

The i-like workshop 2018 is the sixth edition of a yearly series of workshops dedicated to the topic of intractable likelihoods, hosted by Newcastle University. The workshop will take place from Wednesday 20 June 2018 – Friday 22 June 2018 in Room 2.98, Armstrong Building, Newcastle upon Tyne. Registration is free and mandatory!

I spent a few days in Newcastle at the RSS meeting of 2013, with my friends Jim Hobert and Elias Moreno. Enjoying very much the city, its surroundings, the great meadow north of the city in a glorious sunset (I still bemoan not catching on camera!). And it is just in the vicinity of Hadrian’s Wall, just on the other side of the Borders, very close to Edinburgh in fact.

bitcoin and cryptography for statistical inference and AI

Posted in Books, Mountains, pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , on April 16, 2018 by xi'an

A recent news editorial in Nature (15 March issue) reminded me of the lectures Louis Aslett gave at the Gregynog Statistical Conference last week, on the advanced use of cryptography tools to analyse sensitive and private data. Lectures that reminded me of a graduate course I took on cryptography and coding, in Paris 6, and which led me to visit a lab at the Université de Limoges during my conscripted year in the French Navy. With no research outcome. Now, the notion of using encrypted data towards statistical analysis is fascinating in that it may allow for efficient inference and personal data protection at the same time. As opposed to earlier solutions of anonymisation that introduced noise and data degradation, not always providing sufficient protection of privacy. Encryption that is also the notion at the basis of the Nature editorial. An issue completely missing from the paper, while stressed by Louis, is that this encryption (like Bitcoin) is costly, in order to deter hacking, and hence energy inefficient. Or limiting the amount of data that can be used in such studies, which would turn the idea into a stillborn notion.

Bayesian postdoc in Confœderatio Helvetica

Posted in Mountains, Statistics, Travel, University life with tags , , , , , , , , , on April 13, 2018 by xi'an

Antonietta Mira (Università della Svizzera italiana, Lugano) sent me this call for a postdoctoral position between Villigen, near Zürich, hence this picture) and Lugano:

Postdoctoral Fellow: Data Science/Bayesian Inference on Neutron Spectroscopy Data

Your tasks

The increasing availability of empirical large-scale neutron time-of-flight spectroscopy data and steady improvements in computational capacity have resulted in challenges as well as opportunities. This interdisciplinary SDSC-funded project “Bayesian parameter inference from stochastic models (BISTOM)” aims at developing statistical methods and software for analyzing 4D neutron spectroscopy data of quantum magnets. The project is co-directed by Prof. Dr A. Mira (Data Science Center at USI), Dr C. Albert (Eawag), and Prof. Dr Ch. Rüegg (PSI and Univ. Geneva).

Your profile

  • PhD in physics, statistics, applied mathematics or computer science
  • Solid background in neutron spectroscopy or computational statistics/Bayesian inference
  • Strong computational skills
  • Strong scientific writing and communication skills in English

Your working place will be PSI, Villigen and USI, Lugano.

We offer

Our institution is based on an interdisciplinary, innovative and dynamic collaboration. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure. Your employment contract is initially limited to 2 years, but may be extended up to 4 years in combination with other grants/fellowships e.g. Marie-Curie.

For further information please contact Prof. Dr Christian Rüegg, phone +41 56 310 47 78. Please submit your application online (including CV, list of publications and addresses of referees) for the position as a Postdoctoral Fellow (index no. 3004-00).

in the street for a year

Posted in Mountains, pictures, Travel, University life with tags , , , , , , , , , , on April 13, 2018 by xi'an

Just like about every year, I sent two of my pictures to the photography competition of Paris Dauphine, with not much consideration for the theme “green the future”, and was hence quite surprised to get selected this time! (Almost as much surprised as last year when an almost perfect copy of my picture of the Alcazar Baths of Lady María de Padilla got selected!) As I could travel back from Oxford to attend the opening ceremony, I went there last night, wondering at which of my pictures had been selected (Lac Pavin, Auvergne versus the Quinrang, Skye)…

And so this picture will remain exposed in the street, boulevard Lannes, for the incoming year, meaning I will cross it each time I bike to the university! The 22 other pictures were more in tune with the theme of a green future, like the winning one of a fast moving métro carriage at the station Chemin Vert. Or this simple blade of grass growing from ashes…

And thus the winner is… Continue reading

accelerating MCMC

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , on April 11, 2018 by xi'an

As forecasted a rather long while ago (!), I wrote a short and incomplete survey on some approaches to accelerating MCMC. With the massive help of Victor Elvira (Lille), Nick Tawn (Warwick) and Changye Wu (Dauphine). Survey which current version just got arXived and which has now been accepted by WIREs Computational Statistics. The typology (and even the range of methods) adopted here is certainly mostly arbitrary, with suggestions for different divisions made by a very involved and helpful reviewer. While we achieved a quick conclusion to the review process, suggestions and comments are most welcome! Even if we cannot include every possible suggestion, just like those already made on X validated. (WIREs stands for Wiley Interdisciplinary Reviews and its dozen topics cover several fields, from computational stats to biology, to medicine, to engineering.)

Bayesian goodness of fit

Posted in Statistics, University life, Books, pictures with tags , , , , , , , , , on April 10, 2018 by xi'an


Persi Diaconis and Guanyang Wang have just arXived an interesting reflection on the notion of Bayesian goodness of fit tests. Which is a notion that has always bothered me, in a rather positive sense (!), as

“I also have to confess at the outset to the zeal of a convert, a born again believer in stochastic methods. Last week, Dave Wright reminded me of the advice I had given a graduate student during my algebraic geometry days in the 70’s :`Good Grief, don’t waste your time studying statistics. It’s all cookbook nonsense.’ I take it back! …” David Mumford

The paper starts with a reference to David Mumford, whose paper with Wu and Zhou on exponential “maximum entropy” synthetic distributions is at the source (?) of this paper, and whose name appears in its very title: “A conversation for David Mumford”…, about his conversion from pure (algebraic) maths to applied maths. The issue of (Bayesian) goodness of fit is addressed, with card shuffling examples, the null hypothesis being that the permutation resulting from the shuffling is uniformly distributed if shuffling takes enough time. Interestingly, while the parameter space is compact as a distribution on a finite set, Lindley’s paradox still occurs, namely that the null (the permutation comes from a Uniform) is always accepted provided there is no repetition under a “flat prior”, which is the Dirichlet D(1,…,1) over all permutations. (In this finite setting an improper prior is definitely improper as it does not get proper after accounting for observations. Although I do not understand why the Jeffreys prior is not the Dirichlet(½,…,½) in this case…) When resorting to the exponential family of distributions entertained by Zhou, Wu and Mumford, including the uniform distribution as one of its members, Diaconis and Wang advocate the use of a conjugate prior (exponential family, right?!) to compute a Bayes factor that simplifies into a ratio of two intractable normalising constants. For which the authors suggest using importance sampling, thermodynamic integration, or the exchange algorithm. Except that they rely on the (dreaded) harmonic mean estimator for computing the Bayes factor in the following illustrative section! Due to the finite nature of the space, I presume this estimator still has a finite variance. (Remark 1 calls for convergence results on exchange algorithms, which can be found I think in the just as recent arXival by Christophe Andrieu and co-authors.) An interesting if rare feature of the example processed in the paper is that the sufficient statistic used for the permutation model can be directly simulated from a Multinomial distribution. This is rare as seen when considering the benchmark of Ising models, for which the summary and sufficient statistic cannot be directly simulated. (If only…!) In fine, while I enjoyed the paper a lot, I remain uncertain as to its bearings, since defining an objective alternative for the goodness-of-fit test becomes quickly challenging outside simple enough models.