revisiting marginalisation paradoxes [Bayesian reads #1]

As a reading suggestion for my (last) OxWaSP Bayesian course at Oxford, I included the classic 1973 Marginalisation paradoxes by Phil Dawid, Mervyn Stone [whom I met when visiting UCL in 1992 since he was sharing an office with my friend Costas Goutis], and Jim Zidek. Paper that also appears in my (recent) slides as […]

Ian McKellen (2) vs. Ellen DeGeneres; Pierre-Simon Laplace advances

The arguments yesterday in favor of Laplace were valid, earnest, and boring. Dalton reinforced the contrast with this comment: Belushi’s demons are a whole lot more interesting than Laplace’s demon. With the latter, you always know what you’re gonna get forever and ever evermore. The former offers heaps of exciting uncertainty, and if you remember […]

PDSwR2: New Chapters!

We have two new chapters of Practical Data Science with R, Second Edition online and available for review! The newly available chapters cover: Data Engineering And Data Shaping – Explores how to use R to organize or wrangle data into a shape useful for analysis. The chapter covers applying data transforms, data manipulation packages, and … Continue reading PDSwR2: New Chapters!

information maximising neural networks summaries

After missing the blood moon eclipse last night, I had a meeting today at the Paris observatory (IAP), where we discussed an ABC proposal made by Tom Charnock, Guilhem Lavaux, and Benjamin Wandelt from this institute. “We introduce a simulation-based machine learning technique that trains artificial neural networks to find non-linear functionals of data that […]

Pierre-Simon Laplace (2) vs. John Belushi; Pele advances

For yesterday I was leaning toward Penn and Teller based on Bobbie’s reasoning: Penn & Teller not only create interesting, often politically-relevant, magic. They are also visible skeptics who critique the over-claiming of magicians/mystics/paranormal advocates and they use empirical arguments/demonstrations when they speak to debunk pseudoscience. For those of us who care about such things […]

The Stan Core Roadmap

Here’s the plan for Stan core development that Bob presented at Stancon last week (that is, back at the end of August, 2018): Part I. Rear-View Mirror Stan 2.18 Released Multi-core Processing has Landed! Multi-Process Parallelism Map Function New Built-in Functions Manuals to HTML Improved Effective Sample Size Foreach Loops Data-qualified Arguments Bug Fixes and […]

Normal approximation to Laplace distribution?

I heard the phrase “normal approximation to the Laplace distribution” recently and did a double take. The normal distribution does not approximate the Laplace! Normal and Laplace distributions A normal distribution has the familiar bell curve shape. A Laplace distribution, also known as a double exponential distribution, it pointed in the middle, like a pole […]

Facial feedback is back

Fritz Strack points us to this new paper, A multi-semester classroom demonstration yields evidence in support of the facial feedback effect, by Abigail Marsh, Shawn Rhoads, and Rebecca Ryan, which begins with some background: The facial feedback effect refers to the influence of unobtrusive manipulations of facial behavior on emotional outcomes. That manipulations inducing or […]

the paper where you are a node

Sophie Donnet pointed out to me this arXived paper by Tianxi Li, Elizaveta Levina, and Ji Zhu, on a network resampling strategy for X validation, where I appear as a datapoint rather than as a [direct] citation! Which reminded me of the “where you are the hero” gamebooks with which my kids briefly played, before […]

Probabilisitic Identifiers in CCPA

The CCPA, the California Privacy Protection Act, was passed last year and goes into effect at the beginning of next year. And just as the GDPR impacts businesses outside Europe, the CCPA will impact businesses outside California. The law specifically mentions probabilistic identifiers. “Probabilistic identifier” means the identification of a consumer or a device to a […]

Font Fingerprinting

Web sites may not be able to identify you, but they can probably identify your web browser. Your browser sends a lot of information back to web servers, and the combination of settings for a particular browser are usually unique. To get an idea what information we’re talking about, you could take a look at […]

permanent position for research on computational statistics and “omics” data

There is an opening at the French agronomy and genetics research centre, INRA, for a permanent research position on the country campus of Joyu-en-Josas, south-west of Paris, with focus on computational statistics (incl. machine-learning) and collaborations on omics data. The deadline is March 4. (The procedure is somewhat involved, as detailed in the guide for […]