Author: xi'an

bootstrap in Nature

A news item in the latest issue of Nature I received about Brad Efron winning the “Nobel Prize of Statistics” this year. The bootstrap is certainly an invention worth the recognition, not to mention Efron’s contribution to empirical Bayes analysis,, even though I remain overall reserved about the very notion of a Nobel prize in […]

Le Monde puzzle [#1076]

A cheezy Le Monde mathematical puzzle : (which took me much longer to find [in the sense of locating] than to solve, as Warwick U does not get a daily delivery of the newspaper [and this is pre-Brexit!]): Take a round pizza (or a wheel of Gruyère) cut into seven identical slices and turn one […]

a question from McGill about The Bayesian Choice

I received an email from a group of McGill students working on Bayesian statistics and using The Bayesian Choice (although the exercise pictured below is not in the book, the closest being exercise 1.53 inspired from Raiffa and Shlaiffer, 1961, and exercise 5.10 as mentioned in the email): There was a question that some of […]

Binomial vs Bernoulli

An interesting confusion on X validated where someone was convinced that using the Bernoulli representation of a sequence of Bernoulli experiments led to different posterior probabilities of two possible models than when using their Binomial representation. The confusion actually stemmed from using different conditionals, namely N¹=4,N²=1 in the first case (for a model M¹ with […]

a new method to solve the transformation of calculus

An hilariously ridiculous email I just received (warning: book cover unrelated): Good day! this is very important to the “Mathematics” and the related fields, “The Simulator”,“Probability theory”,”Statistics”,”Numerical Analysis”, “Cryptography”,“Data mining”,“The big data analysis”and“Artificial Intelligence”. The transformation of random variables in Calculus is very difficult and sometimes is impossible to be done. The simulator can get […]

“more Bayesian” GANs

On X validated, I got pointed to this recent paper by He, Wang, Lee and Tiang, that proposes a new form of Bayesian GAN. Although I do not see it as really Bayesian, as explained below. “[The] existing Bayesian method (Saatchi & Wilson, 2017) may lead to incompatible conditionals, which suggest that the underlying joint […]

approximate likelihood perspective on ABC

George Karabatsos and Fabrizio Leisen have recently published in Statistics Surveys a fairly complete survey on ABC methods [which earlier arXival I had missed]. Listing within an extensive bibliography of 20 pages some twenty-plus earlier reviews on ABC (with further ones in applied domains)! “(…) any ABC method (algorithm) can be categorized as either (1) […]

a glaringly long explanation

It is funny that, when I am teaching the rudiments of Bayesian statistics to my undergraduate students in Paris-Dauphine, including ABC via Rasmus’ socks, specific questions about the book (The Bayesian Choice) start popping up on X validated! Last week was about the proof that ABC is exact when the tolerance is zero. And the […]