International Society for Bayesian Analysis

As I wanted to simulate truncated normals in a hurry, I coded the inverse cdf approach:

truncnorm=function(a,b,mu,sigma){ u=runif(1) u=qnorm(pnorm((a-mu)/sigma)*(1-u)+u*pnorm((b-mu)/sigma)) return(mu+sigma*u) }

instead of using my own accept-reject algorithm. Poor shortcut as the method fails when a and b are too far from μ

> truncnorm(1,2,3,4) [1] -0.4912926 > truncnorm(1,2,13,1) [1] Inf

So I introduced a control (and ended up wasting more time than if I had used my optimised accept-reject version!)

truncnorm=function(a,b,mu,sigma){ u=runif(1) if (pnorm((b-mu)/sigma)-pnorm((a-mu)/sigma)>0){ u=qnorm(pnorm((a-mu)/sigma)*(1-u)+u*pnorm((b-mu)/sigma)) }else{ u=-qnorm(pnorm(-(a-mu)/sigma)*(1-u)-u*pnorm(-(b-mu)/sigma))} return(mu+sigma*u) }

As shown by the above, it works, even when a=1, b=2 and μ=20. However, this eventually collapses as well and I ended up installing the msm R package that includes rtnorm, an R function running my accept-reject version. (This package was written by Chris Jackson from the MRC Unit in Cambridge.)

Filed under: R, Statistics Tagged: Monte Carlo Statistical Methods, msm package, quantile function, R, rtnorm function, simulation, truncated normal

Here is a short discussion I wrote yesterday with Judith Rousseau of a paper by Peter Müller and Riten Mitra to appear in Bayesian Analysis.

“We congratulate the authors for this very pleasant overview of the type of problems that are currently tackled by Bayesian nonparametric inference and for demonstrating how prolific this field has become. We do share the authors viewpoint that many Bayesian nonparametric models allow for more flexible modelling than parametric models and thus capture finer details of the data. BNP can be a good alternative to complex parametric models in the sense that the computations are not necessarily more difficult in Bayesian nonparametric models. However we would like to mitigate the enthusiasm of the authors since, although we believe that Bayesian nonparametric has proved extremely useful and interesting, we think they oversell the “nonparametric side of the Force”! Our main point is that by definition, Bayesian nonparametric is based on prior probabilities that live on infinite dimensional spaces and thus are never completely swamped by the data. It is therefore crucial to understand which (or why!) aspects of the model are strongly influenced by the prior and how.

As an illustration, when looking at Example 1 with the censored zeroth cell, our reaction is that this is a problem with no proper solution, because it is lacking too much information. In other words, unless some parametric structure of the model is known, in which case the zeroth cell is related with the other cells, we see no way to infer about the size of this cell. The outcome produced by the authors is therefore unconvincing to us in that it seems to only reflect upon the prior modelling (α,G*) and not upon the information contained in the data. Now, this prior modelling may be to some extent justified based on side information about the medical phenomenon under study, however its impact on the resulting inference is palatable.

Recently (and even less recently) a few theoretical results have pointed out this very issue. E.g., Diaconis and Freedman (1986) showed that some priors could surprisingly lead to inconsistent posteriors, even though it was later shown that many priors lead to consistent posteriors and often even to optimal asymptotic frequentist estimators, see for instance van der Vaart and van Zanten (2009) and Kruijer et al. (2010). The worry about Bayesian nonparametrics truly appeared when considering (1) asymptotic frequentist properties of semi-parametric procedures; and (2) interpretation of inferential aspects of Bayesian nonparametric procedures. It was shown in various instances that some nonparametric priors which behaved very nicely for the estimation of the whole parameter could have disturbingly suboptimal behaviour for some specific functionals of interest, see for instance Arbel et al. (2013) and Rivoirard and Rousseau (2012). We do not claim here that asymptotics is the answer to everything however bad asymptotic behaviour shows that something wrong is going on and this helps understanding the impact of the prior. These disturbing bad results are an illustration that in these infinite dimensional models the impact of the prior modelling is difficult to evaluate and that although the prior looks very flexible it can in fact be highly informative and/or restrictive for some aspects of the parameter. It would thus be wrong to conclude that every aspect of the parameter is well-recovered because some are. It has been a well-known fact for Bayesian parametric models, leading to extensive research on reference and other types of objective priors. It is even more crucial in the nonparametric world. No (nonparametric) prior can be suited for every inferential aspect and it is important to understand which aspects of the parameter are well-recovered and which ones are not.

We also concur with the authors that Dirichlet mixture priors provide natural clustering mechanisms, but one may question the “natural” label as the resulting clustering is quite unstructured, growing in the number of clusters as the number of observations increases and not incorporating any prior constraint on the “definition” of a cluster, except the one implicit and well-hidden behind the non-parametric prior. In short, it is delicate to assess what is eventually estimated by this clustering methods.

These remarks are not to be taken criticisms of the overall Bayesian nonparametric approach, just the contrary. We simply emphasize (or recall) that there is no such thing as a free lunch and that we need to post the price to pay for potential customers. In these models, this is far from easy and just as far from being completed.”

References

• Arbel, J., Gayraud, G., and Rousseau, J. (2013). Bayesian adaptive optimal estimation using a sieve prior. Scandinavian Journal of Statistics, to appear.

• Diaconis, P. and Freedman, D. (1986). On the consistency of Bayes estimates. Ann. Statist., 14:1-26.

• Kruijer, W., Rousseau, J., and van der Vaart, A. (2010). Adaptive Bayesian density estimation with location-scale mixtures. Electron. J. Stat., 4:1225-1257.

• Rivoirard, V. and Rousseau, J. (2012). On the Bernstein Von Mises theorem for linear functionals of the density. Ann. Statist., 40:1489-1523.

• van der Vaart, A. and van Zanten, J. H. (2009). Adaptive Bayesian estimation using a Gaussian random field with inverse Gamma bandwidth. Ann. Statist., 37:2655-2675.

Filed under: Statistics Tagged: asymptotics, Bayesian Analysis, Bayesian non-parametrics, Bernstein-von Mises theorem, consistency, Dirichlet mixture priors, Dirichlet process, flexibility, inconsistent priors, non-parametric prior, prior modelling, robustness

A video made in Padova:(and shown during a break at the workshop), watch out for Bayes’ theorem!

Filed under: Books, Kids, Running, Statistics, University life Tagged: Bayes theorem, International Year of Statistics, Padova, The Monty Hall problem

As surprising as it may sound, The House of Silk is a new Sherlock Holmes novel. Obviously, it is not a long forgotten piece of Arthur Conan Doyle, but a pastiche commandeered by the Conan Doyle Estate and written by Anthony Horowitz.I was not at all aware of this book when I came upon it in an Oxford bookstore and bought it on a whim, having always loved Sherlock Holmes’ stories (although George Casella was a much more knowledgeable fan than I).

“I am a mathematician, Dr. Watson. I do not flatter myself when I say that my work on the Binomial Theorem is studied in most of the universities of Europe.” The House of Silk, p.259.

Even though it would be difficult to confuse the style with Conan Doyle’s, and while the story is more involved and contemporary than the original ones, the book is well-written, reasonably coherent within the early 20th Century, and gripping enough to keep me up late over a few evenings. The House of Silk obviously has the advantage to come after the whole sequence of Conan Doyle’s stories and it hence borrows the settings and the characters from this universe: the Baker Street irregulars, Lestrade, Mycroft, and even Moriarty. The story is as usual told by (an old) Watson, recollecting upon events that “were simply too shocking, too monstrous to appear in print” and which could “tear apart the fabric of society”. A clever touch is that Watson describes this story as a mix of two adventures, The Man in the Flat Cap and The House of Silk,  which become linked due to an unfortunate coincidence. As mentioned above, the setting of The House of Silk—if not of The Man in the Flat Cap—is much darker than in an original Holmes novel and uncovers crimes that could not have been mentioned or even alluded to in a Victorian novel. Even the ill-fatted visit of Holmes to an opium den or his dramatic arrest would have sounded too shocking for his time. However, this contributes to the appeal of the novel. (So does the side entry into Watson’s life after his wedding, esp. the lines when he is ask to swear upon what’s most sacred to him and when Holmes’ friendship wins over his marriage…) It actually becomes difficult to criticise aspects of the book like lack of depth in most characters, short scenes, caricatural mistakes in reasoning by Watson, impossibilities, &tc. without realising they could also be addressed to Conan Doyle himself! Hence, if reading that “the game’s afoot” still conjures for you an addictive flavour of mystery, clever sleuthing, and pipe tobacco, I think you will enjoy The House of Silk! As for the Binomial Theorem, I am afraid nothing more is said about it within this book. (In another pastiche, Moriarty actually denies any link with this antique theorem.)

Filed under: Books Tagged: Binomial theorem, book review, James Moriarty, Sherlock Holmes, Watson

While I was editing our “famous” In praise of the referee paper—well, famous for being my most rejected paper ever!, with one editor not even acknowledging receipt!!—for the next edition of the ISBA Bulletin—where it truly belongs, being in fine a reply to Larry’s tribune therein a while ago—, Dimitris Politis had written a column for the IMS Bulletin—March 2013 Issue, page 11—on Refereeing and psychoanalysis.

Uh?! What?! Psychoanalysis?! Dimitris’ post is about referees being rude or abusive in their report, expressing befuddlement at seeing such behaviour in a scientific review. If one sets aside cases of personal and ideological antagonisms—always likely to occur in academic circles!—, a “good” reason for referees to get aggressively annoyed to the point of rudeness is sloppiness of one kind or another in the paper under review. One has to remember that refereeing is done for free and with no clear recognition in the overwhelming majority of cases, out of a sense of duty to the community and of fairness for having our own papers refereed. Reading a paper where typos abound, where style is so abstruse as to hide the purpose of the work, where the literature is so poorly referenced as to make one doubts the author(s) ever read another paper, the referee may feel vindicated by venting his/her frustration at wasting one’s time by writing a few vitriolic remarks.  Dimitris points out this can be very detrimental to young researchers. True, but what happened to the advisor at this stage?! Wasn’t she/he supposed to advise her/his PhD student not only in conducting innovative research but also in producing intelligible outcome and in preparing papers suited for the journal it is to be submitted to..?! Being rude and aggressive does not contribute to improve the setting, no more than headbutting an Italian football player helps in winning the World Cup, but it may nonetheless be understood without resorting to psychoanalysis!

Most interestingly, this negative aspect of refereeing—that can be curbed by posterior actions of AEs and editors—would vanish if some of our proposals were implemented, incl. making referee’ reports part of the referee’s publication list, making those reports public as comments on the published paper (if published), and creating repositories or report commons independent from journals…

Filed under: Statistics, University life Tagged: IMS, ISBA, referee, refereeing, young researchers

Sometimes, if not that often, I forget about submitted papers to the point of thinking they are already accepted. This happened with the critical analysis of Murray Aitkin’s book Statistical Inference, already debated on the ‘Og, written with Andrew Gelman and Judith Rousseau, and resubmitted to Statistics and Risk Modeling in November…2011. As I had received a few months ago a response to our analysis from Murray, I was under the impression it was published or about to be published. Earlier this week I started looking for the reference in connection with the paper I was completing on the Jeffreys-Lindley paradox and could not find it. Checking emails on that topic I then discovered the latest one was from Novtember 2011 and the editor, when contacted, confirmed the paper was still under review! As it got accepted only a few hours later, my impression is that it had been misfiled and forgotten at some point, an impression reinforced by an earlier experience with the previous avatar of the journal, Statistics & Decisions. In the 1990′s George Casella and I had had a paper submitted to this journal for a while, which eventually got accepted. Then nothing happened for a year and more, until we contacted the editor who acknowledged the paper had been misfiled and forgotten! (This was before the electronic processing of papers, so it is quite plausible that the file corresponding to our accepted paper went under a drawer or into the wrong pile and that the editor was not keeping track of those accepted papers. After all, until Series B turned submission into an all-electronic experience, I was using a text file to keep track of daily submissions…) If you knew George, you can easily imagine his reaction when reading this reply… Anyway, all is well that ends well in that our review and Murray’s reply will appear in Statistics and Risk Modeling, hopefully in a reasonable delay.

Filed under: Books, Statistics, University life Tagged: Bayesian Analysis, book review, George Casella, Murray Aitkin, refereeing, rejection, statistical inference

If you have missed the item of information, Håvard Rue is giving an ISBA webinar tomorrow on INLA:

the ISBA Webinar on INLA is scheduled for April 4th, 2013 from 8:30 - 12:30 EDT. ------------------------------------------------------- To join the online meeting (Now from mobile devices using the Cisco WebEx Meeting App) ------------------------------------------------------- 1. Go to https://www.webex.com/login/attend-a-meeting 2. Enter the meeting number 730 293 070 and click Join Now 3. Enter your name and email address, the meeting password and click "Join Now" A recording of the webinar will be provided shortly after the event. Please verify that your computer is capable of connecting using WebEx at https://support.webex.com/MyAccountWeb/systemRequirement.do?root=Tools&parent=System or see https://www.webex.com/login/join-meeting-tips if you are having trouble connecting.
Filed under: R, Statistics, University life Tagged: Havard Rue, INLA, ISBA, Laplace's approximation, online meeting, R-INLA, webinar

Over the last Sunday breakfast I went through Naked Statistics: Stripping the Dread from the Data. The first two pages managed to put me in a prejudiced mood for the rest of the book. To wit: the author starts with some math bashing (like, no one ever bothers to tell us about the uses of high school calculus!) either because he really feels like this or because it pays with the intended audience (like, we are on the same side, pal!), he then shows how he outsmarted his high school math teacher by spotting the exam was not possibly designed for his class and then another math teacher by just… re-inventing the steps leading to Zeno’s paradox (said Zeno of Elea not appearing in the credits of the book, to be sure) and sums it up with an NRA argument: “statistics is like a high-caliber weapon: helpful when used correctly” (p.xiv). Add to that a highly ethnocentric perspective that makes the book hardly readable for anyone outside the US, due to its absolute focus on all things American (exaggerating just a wee bit: who are Lebron James, Kim Kardashian, and Dan Rather?! what is Netflix?! why’s this Donald Rumsfeld guy quoted throughout the book?! how do they play baseball?! What do NBA, NHL, and SAT stand for?! &tc.)—as best illustrated by the facts that it took Charles Wheelan three months to realise a (golf) laser measuring instrument he had received could be in another unit that feet, namely meters!, and that he considers paying 100 rupees for a chai (मसाला चाय) in India a cheap price when this amount roughly corresponds to the average daily salary there…—. Top the whole thing with the fact that the author has already written a Naked Economics and seemingly found gold. (I am desperate for the incoming Naked  Paleopathology tome in the series!) And there you get me stuck with such a highly negative a priori about Naked Statistics that I could not shake it off for the rest of the book.

“This book will not make you a statistical expert (…) This book is not a textbook.” (p.xv)

With this warning in mind about my bias, let’s get on with what’s in this book. The above tells us what isn’t. To quote further from the author, the book “has been designed to introduce the statistical concepts with the most relevance to everyday life“ (p.xv). Naked Statistics goes over the basic notions of statistics (mean, standard deviation, correlation, linear regression, testing, design, polling), gives a sprinkle of probability background (counting models and the central limit theorem, which Wheelan considers as part of statistics), and spend the remaining chapters warning the reader(s) about the possible missuses of models and statistical tools if implemented in the wrong situations or with the wrong type of data. (There are a few graphs, but they are not particularly inspiring.) All this done with the minimum amount of maths formulae, mostly hidden in footnotes and appendices. (But then why adding an extra formula for σ when one is given just before for σ²?!) Sometimes, the minimum is not enough, as demonstrated by the “formula for calculating the correlation coefficient” (p.61) which takes a whole page of text to get around this absurdity of not using maths symbols like Σ and concludes with the lame “I’ll wave my hands and let the computer do the work” (p.61)! Somehow surprisingly, given the low-key nature of the book, it includes a final appendix on statistical software. From Excel, to SAS, Stata, and …R! While I am pleased at this inclusion, it sounds very much orthogonal to the purpose and the intended audience of Naked Statistics. I cannot fathom anyone reading the book and then immediately embarking upon writing an R code without stopping by a statistics textbook or formal training. (Incidentally, the author reproduces the usual confusion between free and open source, p.259.)

“Lest you hurl the book across the room again, I have put the formula in an appendix.” (p.159)

In the chapter about possible misuses of probability models (and statistics), Naked Statistics predictably takes the example of the “most irresponsible use of statistics”, namely the role of inappropriate VAR models in the 2008 crisis. Somehow inevitably, Nassim Taleb’s The Black Swan: The Impact of the Highly Improbable slides in to dispense its widsom. (As an aside, in this chapter, I tried to make sense of the mindboggling sentence “My mother has had three holes in one” (p.99) and could not. Until I found on Google it was a golfing expression…) While the book abounds in reasonable examples on the misuse of statistics, I am not convinced this is the most relevant one, esp. because those unrealistic models were so very rarely based on any data.

“Regression analysis is the hydrogen bomb of the statistics arsenal.” (p.213)

One chapter that proved useful to me was Chapter 5: “Don’t buy the extended warranty on your $99 printer”. Indeed, on the same afternoon I read Naked Statistics, I went to buy an electrical appliance and could bring the book as an argument to refuse this extra-warranty the seller was really eager to let me “benefit from”, for a mere 1/6th of the cost..! (I also liked the trick of Schiltz beer to apparently induce [some] Bud drinkers into switching to this competitor brand.) On the other hand, while I could not spot any statistical blunder from my breakfast cursory read, I did not agree with Wheelan calling “Delma Kinney, a fifty-year-old Atlanta man [who] won $1 million in an instant lottery game in 2008 and another $1 million in an instant lottery game in 2011″ (p.9) a “statistical anomaly”. The probability of “q in 25 trillion” advanced right after is a typical example of the wrong type of conditioning: as explained in several posts on the ‘Og, such occurrences are bound to happen, sometime, somewhere, if most likely not to Mr Delma Kinney!

“The resulting performances will be closer to the mean.” (p.106)

In conclusion, while I do not see much specific appeal in Naked Statistics, I reckon this is one of many books pointing out the possible misuses of statistics to the general public and bringing some awareness as how to re-analyse and debunk (with the proper amount of training) statistics found on the news. In that respect, it does not differ so much (in spirit) from How to lie with Statistics, even though the current book has more current real-life examples. That may be used in the classroom if needed.

Filed under: Books, R, Statistics, University life Tagged: book review, general public, How to Lie with Statistics, India, introductory textbooks, masala chai, Naked Economics, Naked Statistics, Zen, Zeno's paradox

The #814 Le Monde math puzzle was to find 100 digits (between 1 and 10) such that their sum is equal to their product. Given the ten possible values of those digits, this is equivalent to finding integers a1,…,a10 such that

a1+…+a10=100

and

a1+2a2+…+10a10=2a2x….x10a10,

which reduces the number of unknowns from 100 to 10 (or even 9). Furthermore, the fact that the (first) sum of the ai‘s is less than 100 implies that the (second) sum of the iai‘s is less than 1000, hence iai is less than 1000. This reduces the number of possible ten-uplets enough to allow for an enumeration,  hence the following R code:

bounds=c(100,trunc(log(1000)/log(2:10))) for (i2 in 0:bounds[2]) for (i3 in 0:bounds[3]) for (i4 in 0:bounds[4]) for (i5 in 0:bounds[5]) for (i6 in 0:bounds[6]) for (i7 in 0:bounds[7]) for (i8 in 0:bounds[8]) for (i9 in 0:bounds[9]) for (i10 in 0:bounds[10]){ A=c(i2,i3,i4,i5,i6,i7,i8,i9,i10) if (sum(A)<101){ A=c(100-sum(A),A) if (sum((1:10)*A)==prod((1:10)^A)) print(A) }}

that produces two answers

[1] 97 0 0 2 0 0 1 0 0 0 [1] 95 2 3 0 0 0 0 0 0 0

i.e. either 97 1′s, 2 4′s and 1 7, or 95 1′s, 2 2′s and 3 3′s. I would actually love to see a coding solution that does not involve this pedestrian pile of “for”. And a mathematical solution based on Diophantine equations. Rather than the equally pedestrian solution given by Le Monde this weekend.

Filed under: Books, Kids, R Tagged: Diophantine equations, Le Monde, mathematical puzzle, R

Here’s an email from Ben, about my misuse and abuse of the Scottish adjective wee:

As a Scotsman, I was very happy to see your adoption of this great Scottish word, however I noticed in a few places you use it slightly wrongly – in particular, if you use it to describe a noun then you can say for example, “a wee problem”. However if you use it with an adjective you have to use the word “bit” after it – for example, we would say “it’s a wee bit rainy” and not “it’s a wee rainy”.

Ta’, Ben! I stand corrected.

Filed under: Statistics Tagged: Scotland, Scottish, wee, wee bit

Filed under: Kids, pictures, Running, Travel Tagged: Italia, murals, Padova

During my trips in the recent weeks, I managed to read a few books, although nothing spectacular:

Arnaldur Indriðason’s Outrage (Myrká in Icelandic) is a thriller in the Erlandur series, where inspector Erlundur does not appear at all but is replaced with inspector Elinborg who deals with the murder of a drug rapist. And her family problems. The book got a prize in France and its focus on women issues makes it more interesting than the polce story itself, which meanders quite a lot and relies on too many coincidences. But I do like the stuffing no-exit (huis clos) atmosphere. (The above image is the critique in French from Le Canard Enchaîné.) Given that Erlundur has disappeared, this book stands in between other Indriðason’s books, Hypothermia (Harðskafi) and Black Skies (Svörtuloft).

I had mentioned my uneasiness about Hoffman’s The Left Hand of God a few months ago, both because of a very uneven style, a plot borrowing so much to real events and locations, and a highly ambiguous central character. I nonetheless read the second tome, The Last Four Things, following a request from my son. My impression has definitely not improved, mostly again for a high rate of borrowing from existing facts and places (like Chartres used for the papal seat). The title itself is found in many books and comes from a painting by Bosch I missed in Madrid last time I visited El Prado. The characters are mostly the same ones as in The Left Hand of God and they remain shallow and unconvincing. The political plot(s) are of no interest whatsoever. The reunion between Cale and Arbell is botched, to say the least. (And still some people love it!)

Another thriller I quickly read is Susanna Gregory’s Mystery in the Minster, the 17th chronicle of Matthew Bartholomew… In line with the recent chronicles in the series, the book is not worth any level of recommendation. The plots get thinner and thinner, the dialogues and settings less and less realistic for their 14th Century environment, and the resolution is rushed with no even a pretence of disguise for the massive infodump in the Epilogue! It feels like I have already seen it all in previous books: the trip away from Cambridge to gather an uncertain inheritance, the flow of new characters taking an unreasonable interest in Michelhouse affairs, an endless sequence of deaths, poisons, “wanton” nuns, attractive women turning into insane murderesses, fights for life in an abandoned and crumbling church, &tc. Among the many implausible facts in the current volume, the vicar-chorals’ obsession with shoes, speaking of “intelligent, liberal people” as in a 21st Century society, or hiring an actor to play the role of a (long dead) priest for more than a month… I will for certain abstain from buying the incoming 18th chronicle, appropriately planned for April the 1st!

When ordering books from amazon.fr for my daughter, I added Ascension, a manga by Shin’ichi Sakamoto about climbing. I was however quite disappointed by the result, both for the silly plot and for the lack of realism in its climbing connection!

Filed under: Books, Mountains Tagged: Arnaldur Indriðason, Ascension, book reviews, Bosch, Cambridge, climbing, Iceland, manga, Matthew Bartholomew, medieval whodunnits, Paul Hoffman, Susanna Gregory, thrillers, York

As I was crossing the street, on my way to Institut Henri Poincaré to attend the Big’MC seminar with talks by Yves Atchadé on confidence intervals on MCMC ouput and Omiros Papaspiliopoulos on exact filtering, I thought the Panthéon had a nice enough background to deserve a picture. I also stopped by a nearby art shop to buy 0.7mm leads for my mechanical pencil and ended up discussing Charles Rennie Mackintosh with the seller, as I was wearing my University of Glasgow sweatshirt…

Filed under: pictures, University life Tagged: 5ième arrondissement, Charles Rennie Mackintosh, Glasgow, IHP, lead, Panthéon, Paris, Sorbonne, University of Glasgow

An announcement for an Icelandic meeting next September, meeting I would have loved to attend (darn!)… This meeting is sponsored by the BayesComp session, of course!!!

We are pleased to announce that the University of Iceland will host the 3rd Workshop on Bayesian Inference for Latent Gaussian Models with Applications (LGM).

The workshop will be held in Reykjavik, Iceland, on September 12-14 2013 at Harpa ~V Reykjavik Concert Hall and Conference Centre:

The emphasized topics of LGM 2013 are:
-Machine learning
-Spatial and spatio-temporal modeling
-Bayesian non-parametrics
-Latent Gaussian models
-The workshop is not restricted to these topics

The invited speakers are:
-Matthias Katzfuß at Universität Heidelberg
-Bani Mallick at Texas A&M University
-Peter Müller at University of Texas
-Michèle Sebag at INRIA Saclay, CNRS
-Matthias Seeger at École Polytechnique Fédérale de Lausanne
-Christopher Wikle at University of Missouri

Registration fees:
Early bird fee before May 21th ~@ 375
Registration fee after May 21th ~@ 440
Student fee ~@ 250

Detailed information on the scientific program, conference field trip, organizing committee, scientific committee and meeting registration is available on the conference web-site:

Filed under: Mountains, R, Statistics, Travel, University life Tagged: conference, Iceland, INLA, latent Gaussian models, Reykjavik

Filed under: pictures, Running, Travel Tagged: fiume fiume Bacchiglione, Italia, Padova, sunrise

My former student Pierre Jacob (now at NUS in Singapore and soon in Oxford, England) got the 2012 PhD thesis Jacques Neveu prize. (Jacques Neveu, French probabilist specialist of Markov chains, was also the founder of the SMAI Probability and Statistics branch, which is why this prize is named after him. SMAI is the French version of SIAM.) As a coincidence, Pierre also got the PhD prize of Fondation Dauphine last week… Great news! And well-deserved rewards.

Filed under: Kids, University life Tagged: Fondation Dauphine, Jacques Neveu, NUS, Oxford, PhD prize, SIAM, SMAI, Université Paris Dauphine

Filed under: pictures, Travel Tagged: Italia, Padova, sant' Antonio basilica, sunrise

Reproducing an email from ISBA (sorry about the confusion purposely created by the title, this is Durham, North Carolina, not Durham, England, just as the London in Bayes 250 in London was London, England, not London, Ontario!):

ISBA announces a special celebration of the 250th anniversary of the presentation (December 23, 1763) of Thomas Bayes’ seminal paper “An Essay towards solving a Problem in the Doctrine of Chances” that will be held at Duke University in conjunction with the O-Bayes 13 Workshop (December 15-19) and EFab@ Bayes250 Workshop (December 15-17). (I am part of the scientific committee for O-Bayes 13!)

Speakers for the anniversary celebration are legendary contributors to the Bayesian literature, spanning a range of fields:

• Stephen Fienberg, Carnegie-Mellon University
• Michael Jordan, University of California, Berkeley
• Christopher Sims, Princeton University
• Adrian Smith, University of London
• Stephen Stigler, University of Chicago

There will be a banquet in the evening, with a speech by Sharon Bertsch McGrayne, noted author of the popular book “The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines and Emerged Triumphant From Two Centuries of Controversy.”

Filed under: Books, Statistics, Travel, University life, Wines Tagged: An Essay towards solving a Problem in the Doctrine of Chances, anniversary, conference, Duke University, Durham, EFab@, ISBA, O'Bayes, Sharon McGrayne, the theory that would not die, Thomas Bayes, USA, workshop

Filed under: pictures, Running, Travel

Next month, Michael Jordan will give an advanced course at CREST-ENSAE, Paris, on Recent Advances at the Interface of Computation and Statistics. The course will take place on April 4 (14:00, ENSAE, Room #11), 11 (14:00, ENSAE, Room #11), 15 (11:00, ENSAE, Room #11) and 18 (14:00, ENSAE, Room #11). It is open to everyone and attendance is free. The only constraint is a compulsory registration with Nadine Guedj (email: guedj[AT]ensae.fr) for security issues. I strongly advise all graduate students who can take advantage of this fantastic opportunity to grasp it! Here is the abstract to the course:

“I will discuss several recent developments in areas where statistical science meets computational science, with particular concern for bringing statistical inference into contact with distributed computing architectures and with recursive data structures :

1. How does one obtain confidence intervals in massive data sets? The bootstrap principle suggests resampling data to obtain fluctuations in the values of estimators, and thereby confidence intervals, but this is infeasible computationally with massive data. Subsampling the data yields fluctuations on the wrong scale, which have to be corrected to provide calibrated statistical inferences. I present a new procedure, the “bag of little bootstraps,” which circumvents this problem, inheriting the favorable theoretical properties of the bootstrap but also having a much more favorable computational profile.

2. The problem of matrix completion has been the focus of much recent work, both theoretical and practical. To take advantage of distributed computing architectures in this setting, it is natural to consider divide-and-conquer algorithms for matrix completion. I show that these work well in practice, but also note that new theoretical problems arise when attempting to characterize the statistical performance of these algorithms. Here the theoretical support is provided by concentration theorems for random matrices, and I present a new approach to matrix concentration based on Stein’s method.

3. Bayesian nonparametrics involves replacing the “prior distributions” of classical Bayesian analysis with “prior stochastic processes.” Of particular value are the class of “combinatorial stochastic processes,” which make it possible to express uncertainty (and perform inference) over combinatorial objects that are familiar as data structures in computer science.”

References are available on Michael’s homepage.

Filed under: Statistics, University life Tagged: Bayesian nonparametrics, bootstrap, CREST, ENSAE, graduate course, Michael Jordan, Paris, PhD course, Stein's method