This post contains my current views on generative artificial intelligence , and Large Language Models in particular. The context is mostly academia, which is about research and teaching. Personal context Generative AI is slowly creeping into my professional workflow, not because I am using it myself (I don't, although I guess that I will, at some point), but because everyone around me is. My…
This note documents my ongoing Tutorials in Applied Statistics with R (and RStudio) , which are aimed at first-year undergraduate social scientists. Three years ago, I published a Data Science with R course that has gone through a few iterations since then. This year, I started teaching a short series of eight tutorials that cover more or less the same ground, although the audience is now…
This note documents the release of the sfReapportion package, which performs areal-weighted interpolation on spatial objects such as census tracts and voting districts. A colleague of mine recently shared some code for a research project on the upcoming municipal elections in France, but the code required the spReapportion package, which has been hard to install and use for a few years, due to…
More and more people are using AI-generated code in their work, without necessarily understanding the security risks that comes with that practice. How AI-generated code happens Generative AI services such as ChatGPT use Large Language Models to generate computer code. These models are ‘trained’ against a dataset of publicly available code . Many users of generative AI do not seem fully aware of…
This year's Ihaka Lecture is about making R work in government . It was delivered by Peter Ellis, the Director of the Statistics for Development Division at the Pacific Community (SPC). A lot of the talk is based on very direct comparisons between R and other software: The purpose of these comparisons is often to assert that R can do many forms of government analytics better than other software…
The igraph R package has reached version 2.0.0. The igraph package is based on a C library, which is now fully available under the newer versions of the package: This major release brings development in line with the igraph C library . Version 1.6.0 of the R package used version 0.9.10 of the C core. The changes in the 0.10 series of the C core are now taken up in version 2.0 of the R package.…
A security issue has been found with how the R language serializes objects, and patched since. The security issue is documented under CVE-2024-27322 . It affects the serialization functions that were advertised in an earlier note . The R Core Team recently reported that the issue has been fixed as of R 4.4.0, and that ‘any attack vector associated with it has been removed.’ This episode is a…
This blog has been silent for a while, and the Covid-19 pandemic has forced me to ditch my R to-do list for 2021 . I did, however, manage to assemble a few R-related things in the past couple of years. This note documents the main one, a Data Science with R (and RStudio) course aimed at social scientists. Historical side note Around two years ago, I was offered to teach R again at Sciences Po, in…
This note lists the main things that I will be doing with R next year. I took some kind of a break from R over the past 18 months. I plan to change that this coming year, and have compiled the following list of things that I want to explore, or come back to. R Markdown While I have fully transitioned towards “tidy data” and its wonderful packages , I am still not the type of R user who works in R…
This note documents how the sample() function has changed since R 3.6.0, and how to reproduce its previous behaviour. A recent blog post by Christian Robert reminded me that R had to fix its sample() function in R 3.6.0 and above. The issue that used to affect the pseudo-random number generator ( PRNG ) at the core of the function is documented in a note by Kellie Ottoboni and Philip B. Stark, “…