Category: Statistics

Computational Bayesian Statistics [book review]

This Cambridge University Press book by M. Antónia Amaral Turkman, Carlos Daniel Paulino, and Peter Müller is an enlarged translation of a set of lecture notes in Portuguese. (Warning: I have known Peter Müller from his PhD years in Purdue University and cannot pretend to perfect objectivity. For one thing, Peter once brought me frozen-solid […]

Voltaire (4) vs. Benoit Mandelbrot; Veronica Geng advances

Yesterday‘s contest was surprisingly tough. I thought of Santa-man and the inventor of the Monte Carlo method as both being strong candidates—but the best comments on both were negative. Phil argued convincingly that there’s no point in inviting Sedaris to speak at Columbia as there are lots of other opportunities to hear the guy, and […]

O’Bayes 2019: poster deadline extension

For potential participants to the ISBA O’Bayes 2019 conference in Warwick next June 28 – July 02, that is, almost everyone except the participants who have already submitted!, this post is to announce that the deadline for poster submission has just been extended till March 15, to account for BNP 12 potential participants having not […]

missing digit in a 114 digit number [a Riddler’s riddle]

A puzzling riddle from The Riddler (as Le Monde had a painful geometry riddle this week): this number with 114 digits 530,131,801,762,787,739,802,889,792,754,109,70?,139,358,547,710,066,257,652,050,346,294,484,433,323,974,747,960,297,803,292,989,236,183,040,000,000,000 is missing one digit and is a product of some of the integers between 2 and 99. By comparison, 76! and 77! have 112 and 114 digits, respectively. While 99! has 156 digits. […]

alternatives to EM

In an arXived preprint submitted to Computational Statistics & Data Analysis, Chan, Han, and Lim study alternatives to EM for latent class models. That is, mixtures of products of Multinomials. (First occurrence of an indicator function being called the “Iverson bracket function”!) The introduction is fairly extensive given this most studied model. The criticisms of […]

3,000th blog post

I just saw that I’d written 2,999 blog posts, so that makes this one the 3,000th. About a year ago was the 10th anniversary, and Tim Hopper wrote his retrospective about my blog. In addition to chronological blog posts, there are about 200 “pages” on the site, mostly technical notes. These include the most popular […]

George H. W. Bush (2) vs. William Carlos Willams; Mel Brooks advances

All of yesterday’s comments favored Mr. Blazing Saddles. Jeff had a good statistics-themed comment: Mel Brooks created Get Smart (along with Buck Henry), which suggests a number of seminar topics of interest to readers of this blog. “Missed It By That Much: Why Predictive Models Don’t Always Pick the Winner” “Sorry About That, Chief: Unconscious […]

“Objective: Generate evidence for the comparative effectiveness for each pairwise comparison of depression treatments for a set of outcomes of interest.”

Mark Tuttle points us to this project by Martijn Schuemie and Patrick Ryan: Large-Scale Population-Level Evidence Generation Objective: Generate evidence for the comparative effectiveness for each pairwise comparison of depression treatments for a set of outcomes of interest. Rationale: In current practice, most comparative effectiveness questions are answered individually in a study per question. This […]

plenary speakers for BayesComp 20[20]

As a co-chair of the incoming ISBA BayesComp 2020 in Gainesville, Florida, 7-10 January 2020. I am very glad to broadcast that the four plenary speakers for the conference are David Blei (Columbia U) Paul Fearnhead (U Lancaster) Emily Fox (U Washington) Max Welling (U Amsterdam) There will soon be a call for contributed sessions, […]

estimation exam [best of]

Yesterday, I received a few copies of our CRC Press Handbook of Mixture Analysis, while grading my mathematical statistics exam 135 copies. Among the few goodies, I noticed the always popular magical equality E[1/T]=1/E[T] that must have been used in so many homeworks and exam handouts by now that it should become a folk theorem. […]

The bullshit asymmetry principle

Jordan Anaya writes, “We talk about this concept a lot, I didn’t realize there was a name for it.” From the wikipedia entry: Publicly formulated the first time in January 2013 by Alberto Brandolini, an Italian programmer, the bullshit asymmetry principle (also known as Brandolini’s law) states that: The amount of energy needed to refute […]

risk-adverse Bayes estimators

An interesting paper came out on arXiv in early December, written by Michael Brand from Monash. It is about risk-adverse Bayes estimators, which are defined as avoiding the use of loss functions (although why avoiding loss functions is not made very clear in the paper). Close to MAP estimates, they bypass the dependence of said […]