Laurent Bergé | Lightnews

Laurent Bergé @lrberge.bsky.social · Oct 2

I feel seen!

Laurent Bergé @lrberge.bsky.social · Sep 24

I use =

Libby Heeren @libbyheeren.bsky.social · Sep 24

Tell me something you do when you code that other people would tell you that you shouldn't do.

Tell me the rules you break!

I'll go first: I work in untitled files in the wrong project directories all the time. Like, all the time. Yes, I do tend to lose things 😂 #databs #rstats #python

Grant McDermott @gmcd.bsky.social · Sep 23

`tinyplot` 0.5.0 is now available from CRAN & R-universe. Alongside bug fixes & internal improvements, this release includes some cool new features like bubble chart + dual legend support, element dodging, & ephemeral themes.

Detailed changelog: grantmcdermott.com/tinyplot/NEW...

#rstats #dataviz

tinyplot bubble chart example with dual legend, using penguins data. Taken from https://grantmcdermott.com/tinyplot/vignettes/gallery.html

Susan Vanderplas @srvanderplas.bsky.social · Sep 15

Sarcasm, but actually something brought up by one of the deans, that having statisticians around is *less* important in the age of AI because AI can just do experimental design and data analysis for researchers. No joke. #sendhelp

Emily Riederer @emilyriederer.bsky.social · Sep 14

Really insightful post from Julie Tibshirani (spotted in LinkedIn, can't find on Bsky) reflecting on #rstats 's unique governance structure and what can be learned for other languages

jtibs.substack.com/p/if-all-the...

If all the world were a monorepo

The R ecosystem and the case for extreme empathy in software maintenance

jtibs.substack.com

Laurent Bergé @lrberge.bsky.social · Sep 12

+100

I don't understand this need to overclaim.

I they want to create a new pkg doing stg already existing: sure no problem, since variety is good.

But falsely claiming that the original pkg is bad.... really incorrect.
And it's typical alas...

Grant McDermott @gmcd.bsky.social · Sep 11

Important note for Mac users: make sure your installation properly exploits `fixest` multi-threading capabilities:

1. Follow @coatless.bsky.social's simple shell script and OpenMP instructions here: github.com/coatless-she...

2. Install from source: `install.packages("fixest", type = "source")`

Laurent Bergé @lrberge.bsky.social · Sep 10

Among the new features:
- new builtin VCOV: HC2 aand HC3 (thanks to Kyle Butts!)
- new function sparse_model_matrix
- improved internal algorithms
- coefplot/iplot become similar to etable
- batched estimations are easier to make

& many many more, check out the news file!
github.com/lrberge/fixe...

Laurent Bergé @lrberge.bsky.social · Aug 24

The EEA conference starts tomorrow in Bordeaux!
I'll be around, so if you want to meet, just reach out!

#rstats #econsky

www.eeassoc.org/events/eea-b...

This link will take you to a page that’s not on LinkedIn

lnkd.in

Laurent Bergé @lrberge.bsky.social · Jul 25

Yep, this is not native.
I had to develop my own VSCode extension to make it work.

Grant McDermott @gmcd.bsky.social · Jul 18

#rstats #econsky PSA: The next release of `fixest` will include some important changes (plus cool new features).

E.g. Fixed-effects regs will now default to 'iid' SEs rather than clustered. github.com/lrberge/fixe...

You can install and test drive the dev version from R-universe; see the README.

From the fixest NEWS file: the new default VCOV is iid for all estimations. To change the default to the way it was, place setFixest_vcov(all = "cluster", no_FE = "iid") in your .Rprofile.

Laurent Bergé @lrberge.bsky.social · Jul 6

For the first use, there is predict.mira that does not seem to exist, so it can be created no problem.

For the second usage, it seems that MI is done to the predict method of a non-MI estimation.
=> I don't see the issue of creating a new function here bc the use case is very specific

Laurent Bergé @lrberge.bsky.social · Jul 4

In general masking any base R (including stats, utils, etc) function is a bad idea bc other packages rely on them and expect them to work in a very specific way.

I don't think what you want is possible because of the way S3 works.
Maybe change the design? It might be the easiest way.

Laurent Bergé @lrberge.bsky.social · Jul 2

Announcing sircon: a new R console! (for Windows)

It's in beta and actively developed (new patched version just released).

I've been using it for a while now and I think it's rather bug free. But if you encounter some: let me know!

github.com/lrberge/sircon

Laurent Bergé @lrberge.bsky.social · Jul 2

It's in beta though but I'm actively developing it. Comments welcome!

BTW to install:
remotes::install_github("https://github.com/lrberge/rmake")

Laurent Bergé @lrberge.bsky.social · Jul 2

Hey, I'm new developing a package to make reproductibility easy.

It's rmake!

Contrary to {targets}, you don't need to set up anything, it is all automatic!

So you can have modular code while writing in a single script!!!

github.com/lrberge/rmake

Laurent Bergé @lrberge.bsky.social · Jun 24

OK, thanks for your answer.

You even comment your gitignore :-), nice! (I never do that, but I should!)

Laurent Bergé @lrberge.bsky.social · Jun 23

This fool's actions may, in the end, just favor the renewable energy sector (due to the change in relative prices).

I love the irony!

Laurent Bergé @lrberge.bsky.social · Jun 23

Sorry for all those questions, thanks for sharing!

Laurent Bergé @lrberge.bsky.social · Jun 23

Did you like the quarto workflow (vàv other ways to create such websites)? Did you cut dev time by using it?

Very nice looking btw, well done!

Laurent Bergé @lrberge.bsky.social · Jun 20

Haha, thanks Grant! But TBH I don't know how soon that will be!

Laurent Bergé @lrberge.bsky.social · Jun 20

There are a few productivity bonuses at the end of the presentation (which was fully written in typst btw), in particular:

- a new way to handle reproductibility in R
- a new R console (!)

Although both projects are in active dev, they work:

github.com/lrberge/rmake

github.com/lrberge/sircon

GitHub - lrberge/rmake

Contribute to lrberge/rmake development by creating an account on GitHub.

github.com

Laurent Bergé @lrberge.bsky.social · Jun 20

Just gave a presentation a the REGIS summer school we organised in Bordeaux.

Algorithms for empirical research

Slides and material here: github.com/lrberge/2025...

The conclusion is that, even in the age of AI, using your brain is still relevant!

#RStats #EconSky

Kyle Butts @kylefbutts.bsky.social · Jun 8

github.com/kylebutts/vs...
If you are using vscode and stata, you should try out my extension. It uses interactive window which let's you write in a `.do` file but get a notebook type experience.

Laurent Bergé @lrberge.bsky.social · Jun 6

Agree. Now grading projects would require individual interactions with the students.

However:
- I don't know how to reach fairness via f2f interactions (many other factors at play)
- this proves impossible for large cohorts

Another nail in the coffin of mass education.

Laurent Bergé @lrberge.bsky.social · Jun 6

Good post that generates discussions on student's use of LLMs.

If you're a teacher, have a look!

Andrew Heiss @andrew.heiss.phd · Jun 5

Updated my "AI, LLMs, and bullshit" mini-lecture post in my dataviz class with a new section on vibe coding datavizs25.classes.andrewheiss.com/resource/ai-...

Vibe coding and learning
Remember that LLMs are (philosophical) bullshit machines. They don’t care if the answer if gives you is wrong or right. They don’t care if the code runs or not. All they care about is if the answer looks plausible.

That said, in part due to the massive amount of publicly available code that’s inside their training data, LLMs can work okay with code in limited circumstances. Think of them as fancy documentation—if a programming language or package has good documentation with lots of good examples online, the stuff that LLMs generate about it will generally have good coverage and won’t be completely made up.

They work well enough that a whole new approach to programming has emerged: vibe coding. When vibe coding, you essentially tell an LLM what you want it to make and then let it actually build the whole thing. Some code editors actually allow LLMs to create and edit files directly on your computer. Like, you can say

Make a website that has a login page where users can log in and then create and edit blog posts. Create a theme for it that is mostly blue, but with some nice contrasting colors, and use a warm, friendly sans serif font. Add some photos from Flickr too.

… and it will attempt to do that, creating all the necessary files and code. It feels neat and magical to code without coding.

If you know what you’re doing, and you mistrust everything the LLM spits out, and hand-check everything it says, vibe coding can save you some time. HOWEVER it is (1) potentially dangerous, and (2) bad for learning.

$Danger! Because LLMs are designed to make plausible looking code, they can reference external packages that don’t exist. For instance, you might want to make a lollipop chart, and it’ll say something like Certainly! First, run remotes::install_github("someone/gglollipop") and then run library(gglollipop) to load it. BUT GUESS WHAT. There is no package named {gglollipop}. It’s not a thing. Malicious actors also vibe code and look for the names of packages that LLMs think should exist, then they go and create those packages themselves, but include malware in those fake packages. If you’re using an editor that allows LLMs to make changes to your computer, it can run all this code without you knowing what happens and bad things can happen. Additionally, vibe-coded code can run well but be full of security vulnerabilities and issues and inefficiencies and bugs. The code it generates is essentially an average of all other code online—it will have bugs and security issues. It’s also incredibly easy to accidentally expose private information to LLMs, like feeding them passwords, usernames, private data, and so on, especially if you’re mindlessly generating and running code. Always distrust and be suspicious about all code that LLMs generate.$

Bad for learning!
Some people claim that vibe coding helps them learn how to code. This is most likely not the case—pure vibe coding likely hurts learning. Think of learning to code like learning a language. You could try to learn French by watching hours and hours of French movies, and you’d certainly pick stuff up, but you won’t learn nearly as well as you would by taking a dedicated French class.

You need the foundation first. If you take a few years of French classes and then watch hours and hours of French movies, you’ll learn a lot. If you jump right into a pure media-based approach to learning, it’ll be detrimental to learning the language.

Recent research explores this idea with LLMs:

Students who substitute some of their learning activities with LLMs (e.g., by generating solutions to exercises) increase the volume of topics they can learn about but decrease their understanding of each topic. Students who complement their learning activities with LLMs (e.g., by asking for explanations) do not increase topic volume but do increase their understanding. We also observe that LLMs widen the gap between students with low and high prior knowledge. (Lehmann, Cornelius, and Sting 2025)

Prior knowledge is essential if you want to do any code-related stuff with LLMs, and even then, LLMs are helpful when asking for explanations (e.g. “This code works, but I don’t know why! Can you explain what’s happening with geom_point() here?”), but far less helpful for learning than just generating plausible-looking answers.

I can typically tell when you submit code generated by an LLM; it has a certain vibe/style to it and often gives you extraneous code that you don’t actually need to use. Like this—this comes right from ChatGPT:

# Load the required libraries
library(dplyr)

# Read a file named cars.csv into the R session
data <- read.csv("data/cars.csv")

# Calculate the average value of cty by class
average_cty_by_class <- data %>%
group_by(class) %>%
summarize(average_cty = mean(cty, na.rm = TRUE), .groups = "drop")

# Show the results
print(average_cty_by_class)

The “tells”
Here’s how I can tell that that ↑ code comes from an LLM:

Comments at every stage
read.csv() instead of read_csv(),
The older %>% pipe instead of the newer |> pipe
na.rm = TRUE inside mean()
.groups = "drop" inside summarize()
Using print() to show the created object
In general, don’t ever just copy/paste from ChatGPT and hope it runs. If you do use these tools, use them to ask for explanations. Make sure you know what every line of code is doing. For example, if it spits out summarize(average_cty = mean(cty, na.rm = TRUE), .groups = "drop"), and you don’t know what those na.rm = TRUE or .groups = "drop" things mean, look at the help page for mean() and see what na.rm actually does so you can decide if you really need to use it or not, or ask the LLM why it included it.

I will call out code that looks vibe-coded in your assignments. Please don’t do it.

Laurent Bergé @lrberge.bsky.social · Jun 6

The pblm is that most students don't care abt learning, they only care abt grades.

Who cares about learning? Students with this character trait, acquired mostly thanks to the family.

With LLM stripping off extrinsic motivation (good grades = work), we end up with yet more tech induced inequality.

Laurent Bergé @lrberge.bsky.social · Jun 6

I fully agree with your approach but then comes the grades.

Students who genuinely try to learn and struggle may get worse grades that others that don't care and use full LLM w/t thinking.

This is highly unfair for the former students and they may suffer from that.

Andrew Heiss @andrew.heiss.phd · Jun 5

Updated my "AI, LLMs, and bullshit" mini-lecture post in my dataviz class with a new section on vibe coding datavizs25.classes.andrewheiss.com/resource/ai-...

$Danger! Because LLMs are designed to make plausible looking code, they can reference external packages that don’t exist. For instance, you might want to make a lollipop chart, and it’ll say something like Certainly! First, run remotes::install_github("someone/gglollipop") and then run library(gglollipop) to load it. BUT GUESS WHAT. There is no package named {gglollipop}. It’s not a thing. Malicious actors also vibe code and look for the names of packages that LLMs think should exist, then they go and create those packages themselves, but include malware in those fake packages. If you’re using an editor that allows LLMs to make changes to your computer, it can run all this code without you knowing what happens and bad things can happen. Additionally, vibe-coded code can run well but be full of security vulnerabilities and issues and inefficiencies and bugs. The code it generates is essentially an average of all other code online—it will have bugs and security issues. It’s also incredibly easy to accidentally expose private information to LLMs, like feeding them passwords, usernames, private data, and so on, especially if you’re mindlessly generating and running code. Always distrust and be suspicious about all code that LLMs generate.$

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