Kamal Romero

Alternatively

Anthropic uses a questionable dark pattern to obtain user consent for AI data use in Claude Anthropic’s new data policy raises legal concerns with its use of questionable dark patterns.

Anthropic uses questionable dark patterns to obtain users’ consent to the use of AI data in Claude: the-decoder.com/anthropic-us...
#Claude #DataProtection

“el comercio internacional no es una guerra de países, sino un mercado gigantesco donde las empresas y los consumidores hacen lo mismo de siempre: vender, comprar y organizarse lo mejor que pueden. Es una liga en la que todos pueden ganar algo.”

Inmigración y crimen: lo que dice la evidencia Entre otros temas, este verano ha estado marcado por la agitación del fantasma de la inmigración por parte de los partidos de ultraderecha. Primero alentando los progromos en Torre Pacheco, después ve...

Desgraciadamente, importantes partidos y medios de comunicación continúan dando eco y espacio a la idea de que la inmigración trae crimen. ¿Pero qué dice la evidencia? A esto respondo en mi nueva entrada en @nadaesgratis.bsky.social
nadaesgratis.es/santiago-san...

Trends and random walks in macroeconmic time series : Some evidence and implications
by Nelson, Charles R. & Plosser, Charles I. (1982)

Charles Plosser, RIP - Marginal REVOLUTION Alas, and still an underrated economist.

Charles Plosser, RIP - Marginal REVOLUTION

Charlie Plosser served as a faculty member and Dean of the Business School at the University of Rochester. He served as editor of the Journal of Monetary Economics (with Bob King), and later the President of the Philadelphia Fed. A serious and sensible economist. RIP.

Charles I. Plosser passed away on August 14, 2025. Here is an obituary www.hoover.org/profiles/cha...

Among his many influential academic contributions, one might mention "Real Business Cycles" (1983, together with John B. Long).

people.bu.edu/rking/EC702/...

ggdiagram: Object-Oriented Diagram Plots with 'ggplot2' Creates diagrams with an object-oriented approach. Geometric objects have computed properties with information about themselves (e.g., their area) or about their relationships with other objects (e.g, the distance between their edges). The objects have methods to convert them to geoms that can be plotted in 'ggplot2'.

New on CRAN: ggdiagram (0.1.0). View at https://CRAN.R-project.org/package=ggdiagram

📝 "Mastering Debugging in R"

👤 Cosima Meyer (@cosima.bsky.social)

📖 Master R debugging! Learn `debug()`, `browser()`, `undebug()`, and visualize code flow with `{flow}`.

🔗 https://cosimameyer.com/post/mastering-debugging-in-r/

#rladies #rstats #oldiebutgoodie

❗️Our next workshop will be on August 28th, 6 pm CEST, on Efficient R by @selina-b.bsky.social
Register or sponsor a student by donating to support Ukraine!
Details: bit.ly/3wBeY4S
Please share!
#AcademicSky #EconSky #RStats

After I set up a Python environment to run LLMs locally with Docker Model Runner, I wondered if you could use the same workflow with R. The short answer is, "Hell Yeah!"

It took me 5 minutes to run LLMs with R using the ellmer library. Working on a step-by-step tutorial...

#RStats #LLM #Docker

library(tidyverse) # Review the data (df). Missing data is denoted by “MR”. df # A tibble: 6 x 6 id form var1 var2 var3 var4 <dbl> <chr> <chr> <chr> <chr> <chr> 1 10 "a" 3 4 3 3 2 11 "b" 3 MR 2 4 3 12 "b" 1 3 1 MR 4 13 "" MR MR MR MR 5 14 "" MR MR MR MR 6 15 "" 1 2 3 MR # (01) Only keep rows where respondent has missing responses for AT LEAST ONE variable (var1:var4). df %>% filter(if_any(var1:var4, ~ . == "MR")) # A tibble: 5 x 6 id form var1 var2 var3 var4 <dbl> <chr> <chr> <chr> <chr> <chr> 1 11 "b" 3 MR 2 4 2 12 "b" 1 3 1 MR 3 13 "" MR MR MR MR 4 14 "" MR MR MR MR 5 15 "" 1 2 3 MR # (02) Only keep rows where respondent has missing responses for ALL variables (var1:var4). df %>% filter(if_all(var1:var4, ~ . == "MR")) # A tibble: 2 x 6 id form var1 var2 var3 var4 <dbl> <chr> <chr> <chr> <chr> <chr> 1 13 "" MR MR MR MR 2 14 "" MR MR MR MR # (03) Remove rows where respondent has missing responses for ALL variables (var1:var4). df %>% filter(!if_all(var1:var4, ~ . == "MR")) # A tibble: 4 x 6 id form var1 var2 var3 var4 <dbl> <chr> <chr> <chr> <chr> <chr> 1 10 "a" 3 4 3 3 2 11 "b" 3 MR 2 4 3 12 "b" 1 3 1 MR 4 15 "" 1 2 3 MR

I often need to filter data in #rstats based on many variables. The dplyr::if_any() and dplyr::if_all() functions are really handy for this.

More examples here: cghlewis.github.io/data-wrangli...

Just an honest labor statistician collecting the data, crunching the numbers, and reporting them fairly, and definitely not an extremist ideologue with an axe to grind, unshackled from respect for the law or political norms.

¿Alguien por acá que esté trabajando o quiere empezar a trabajar con esta librería? Ya he empezado, pero definitivamente voy a pasar todos mis análisis de encuestas de Stata a R {survey}

En mi experiencia (negativa) a este respecto, estas inercias dependen en parte de coordinadores de asignaturas que por un lado no desean aprender otras herramientas, y por el otro, les viene bien que la universidad les pague su herramientad de trabajo. Esto es solo anecdótico, habrá muchas más cosas

I had a great time presenting a #useR2025 workshop with @statsteph.bsky.social and Rebecca Powell on "Complex Survey Data Analysis"!

If you'd like to check out the materials, we cover survey design, descriptive analysis, statistical testing, & more: tidy-survey-r.github.io/user-2025-su...

#RStats

"The fourth problem is that some of those people are investors in financial assets such as inflation-protected securities (TIPS) that are directly linked to the BLS’s estimates of inflation, as well as other assets that depend on the credibility of official US statistics."

"But while Trump’s fans may applaud McEntarfer’s fate as a suitable punishment for faking the numbers, his opponents will view it as opening the door to future fakery. This is the third piece of bad news: there are many people who used to trust the BLS’s numbers, but no longer will"

"First, like much of what Trump does, it serves as a distraction. Second, Trump’s behaviour signals to his supporters that US statistics are not the outcome of an impartial and professional process — they are invented for political reasons and only a fool would take them seriously."

"Trump’s decision — shameless even by his standards — is bad news for at least four reasons. " (continue)

1/ 💡 We just published a new working paper on SSRN exploring how AI is reshaping the architecture of innovation ecosystems.

🔗 dx.doi.org/10.2139/ssrn...

🧵 1/8

There are some R packages that just feel like magic. I first encountered the datapasta package by Miles McBain when I was working with an EMG system that didn’t export the data in a user-friendly format.

It's pretty clear that people are only gay if the marginal benefit is less than the marginal cost of dating men.

Understanding the US net foreign asset position Andrew Atkeson discusses changes in how much the United States is indebted to the rest of the world.

After the Great Recession, the US started accumulating significant liabilities to foreigners. We spoke with Andrew Atkeson of UCLA about how to interpret this trend and what it means for American households. #econsky www.aeaweb.org/research/net...

If you like how Argentina has produced economic statistics, you'll love this guy.

Trump's nominee for BLS commissioner, EJ Antoni, is disastrously terrible. He's a 1200%, 1300% maybe 1400% in-the-tank Trumper, with few credentials beyond a history of misrepresenting or misunderstanding economic statistics. He has shown no commitment to truth
www.washingtonpost.com/business/202...

Trump Nominates EJ Antoni to BLS Commissioner | Econbrowser From CNBC:

Menzie Chinn provides a useful roundup of some of the recent misrepresentations and basic misunderstandings of government statistics from Trump's nominee to be our next BLS Commissioner. The clear theme is a commitment to winning a partisan news cycle over the truth: econbrowser.com/archives/202...

🚨

I have a new paper with a fantastic team (thanks to @jgeller1phd.bsky.social!) with a nice mix of theoretical & applied perspectives on beta regression modeling (i.e., proportions). It's fully reproducible with #rstats code.

Great resource for teaching & self-learning!

osf.io/preprints/ps...