I am off to Venezia this afternoon for a Franco-Italian workshop organised by my friends Monica Billio, Roberto Casarin, and Matteo Iacopini, from the Department of Economics of Ca’ Foscari, almost exactly a year after my previous trip there for ESOBE 2016. (Except that this was before!) Tomorrow, I will give both a tutorial [for the second time in two weeks!] and a talk on ABC, hopefully with some portion of the audience still there for the second part!
Archive for tutorial
back to ca’ Foscari, Venezia
Posted in Books, pictures, Statistics, Travel, University life, Wines with tags ABC, Ca' Foscari University, convergence of ABC, ESOBE, Italia, tutorial, Venezia on October 16, 2017 by xi'anBayes’ Rule [book review]
Posted in Books, Statistics, University life with tags Amazon, Bayes formula, Bayes rule, Bayes theorem, Bayesian Analysis, England, introductory textbooks, publishing, short course, Thomas Bayes' portrait, tutorial on July 10, 2014 by xi'anThis introduction to Bayesian Analysis, Bayes’ Rule, was written by James Stone from the University of Sheffield, who contacted CHANCE suggesting a review
of his book. I thus bought it from amazon to check the contents. And write a review.
First, the format of the book. It is a short paper of 127 pages, plus 40 pages of glossary, appendices, references and index. I eventually found the name of the publisher, Sebtel Press, but for a while thought the book was self-produced. While the LaTeX output is fine and the (Matlab) graphs readable, pictures are not of the best quality and the display editing is minimal in that there are several huge white spaces between pages. Nothing major there, obviously, it simply makes the book look like course notes, but this is in no way detrimental to its potential appeal. (I will not comment on the numerous appearances of Bayes’ alleged portrait in the book.)
“… (on average) the adjusted value θMAP is more accurate than θMLE.” (p.82)
Bayes’ Rule has the interesting feature that, in the very first chapter, after spending a rather long time on Bayes’ formula, it introduces Bayes factors (p.15). With the somewhat confusing choice of calling the prior probabilities of hypotheses marginal probabilities. Even though they are indeed marginal given the joint, marginal is usually reserved for the sample, as in marginal likelihood. Before returning to more (binary) applications of Bayes’ formula for the rest of the chapter. The second chapter is about probability theory, which means here introducing the three axioms of probability and discussing geometric interpretations of those axioms and Bayes’ rule. Chapter 3 moves to the case of discrete random variables with more than two values, i.e. contingency tables, on which the range of probability distributions is (re-)defined and produces a new entry to Bayes’ rule. And to the MAP. Given this pattern, it is not surprising that Chapter 4 does the same for continuous parameters. The parameter of a coin flip. This allows for discussion of uniform and reference priors. Including maximum entropy priors à la Jaynes. And bootstrap samples presented as approximating the posterior distribution under the “fairest prior”. And even two pages on standard loss functions. This chapter is followed by a short chapter dedicated to estimating a normal mean, then another short one on exploring the notion of a continuous joint (Gaussian) density.
“To some people the word Bayesian is like a red rag to a bull.” (p.119)
Bayes’ Rule concludes with a chapter entitled Bayesian wars. A rather surprising choice, given the intended audience. Which is rather bound to confuse this audience… The first part is about probabilistic ways of representing information, leading to subjective probability. The discussion goes on for a few pages to justify the use of priors but I find completely unfair the argument that because Bayes’ rule is a mathematical theorem, it “has been proven to be true”. It is indeed a maths theorem, however that does not imply that any inference based on this theorem is correct! (A surprising parallel is Kadane’s Principles of Uncertainty with its anti-objective final chapter.)
All in all, I remain puzzled after reading Bayes’ Rule. Puzzled by the intended audience, as contrary to other books I recently reviewed, the author does not shy away from mathematical notations and concepts, even though he proceeds quite gently through the basics of probability. Therefore, potential readers need some modicum of mathematical background that some students may miss (although it actually corresponds to what my kids would have learned in high school). It could thus constitute a soft entry to Bayesian concepts, before taking a formal course on Bayesian analysis. Hence doing no harm to the perception of the field.
AI and Statistics 2014
Posted in Kids, Mountains, Statistics, Travel, University life with tags ABC, AISTATS 2014, Iceland, Reykjavik, tutorial, vacations on April 18, 2014 by xi'an
Today, I am leaving Paris for a 8 day stay in Iceland! This is quite exciting, for many reasons: first, I missed the AISTATS 2013 last year as I was still in the hospital; second, I am giving a short short tutorial on ABC methods which will be more like a long (two hours) talk; third, it gives me the fantastic opportunity to visit Iceland for a few days, a place that was top of my wish list of countries to visit. The weather forecast is rather bleak but I am carrying enough waterproof layers to withstand a wee bit of snow and rain… The conference proper starts next Tuesday, April 22, with the tutorials taking place next Friday, April 25. Hence leaving me three completely free days for exploring the area near Reykjavik.
MCQMC2014 in Belgium
Posted in Books, Statistics, Travel, University life with tags ABC, Belgium, KU Leuven, Leuven, Louvain-la-Neuve, MCQMC2014, Monte Carlo methods, quasi-Monte Carlo methods, simulation, tutorial on October 11, 2013 by xi'an
The conference MCQMC2014 (which stands for Monte Carlo and Quasi-Monte Carlo) will take place in Leuven, Belgium, on April 6-11. More exactly, in the Katholieke Universiteit Leuven, which is the Flemish-speaking side of the split (1968) Catholic University of Leuven, the French speaking side Université Catholique de Louvain being located in Louvain-la-Neuve. After missing MCQMC2012 in Sydney, I will attend this conference where I give an invited talk (on ABC, what else..?!). As it happens (and kind of logically), I have visited Louvain-la-Neuve many times, especially in the previous era where historical Bayesians Michel
Mouchard, Jean-Marie Rolin and Léopold Simar were together in the Statistics department—two of them contributing to the highly formalised “Elements of Bayesian Statistics” that I perused during my PhD thesis in Rouen—, but I have never been to Leuven or to KU Leuven,
A great item of news is that one of the two tutorials (on April 6, 2014) will given by Art Owen, the theme being “ANOVA, global sensitivity, Sobol’ indices and all that“, The second tutorial is by Mike Giles (Oxford) on his approach of multi-level Monte Carlo methods. (If the organisers follow the MCQMC2012 trend, the Sunday afternoon tutorials should follow one another.)