R-bloggers

R-bloggers is a platform that leverages the content from various documents to provide concise summaries for its audience. The platform serves as a hub for information and insights related to a wide range of topics. By summarizing the content from diverse sources, R-bloggers aims to offer valuable and easily digestible information to its readers. The platform’s summaries are designed to provide a quick overview of the key points and insights covered in the original documents, making it a convenient resource for individuals interested in staying informed about the latest developments in various fields.

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Schotter Plots in R

R-bloggers

Translating things between languages reveals how each language approaches different design trade-offs, and I believe it’s a useful exercise. Having something to translate is the first step. I found a ...

What’s new in R 4.6.0?

R-bloggers

R 4.6.0 (“Because it was There”) is set for release on April 24th 2026. Here we summarise some of the more interesting changes that have been introduced. In previous blog posts, we have discussed the ...

My Domain: proteome-wide scanning of TMDs

R-bloggers

I wanted to know: After a little bit of searching, I couldn’t find any answers. So I decided to use R to retrieve the necessary info from Uniprot and calculate it myself. I thought I’d post it here in...

Expanding the Editorial Team: Alec Robitaille and Lucy D’Agostino McGowan Join as Editors

R-bloggers

At rOpenSci, we’re continually grateful for the support and engagement of our community, who help make research open-source stronger, more inclusive, and more collaborative. The software peer review p...

Stage II OSCC — Health Economics Model

R-bloggers

Most health care economics models are constructed from the perspective of a managed health care system such as those offered in Canada and several European countries, or from the perspective of some o...

Why Most Time Series Models Fail Before They Start

R-bloggers

1 A model can run and still be fundamentally wrong Many time series models fail before they even begin. Not because the software crashes. Not because the code is wrong. But because the data entering t...

logrittr: A Verbose Pipe Operator for Logging dplyr Pipelines

R-bloggers

dplyr verbs are descriptive: let’s make them more verbose! Yet another pipe for R. Motivation In SAS, every DATA step prints a log: NOTE: There were 120000 observations read from WORK.SALES. NOTE: 715...

Dealing with correlation in designed field experiments: part II

R-bloggers

With field experiments, studying the correlation between the observed traits may not be an easy task. For example, we can consider a genotype experiment, laid out in randomised complete blocks, with 2...

Programming with LLMs in R & Python *[April 11, 2026]: 2026-04-11T07:34:00+1000

R-bloggers

Working with LLMs in Practice Large Language Models are becoming part of everyday data science work. But using them through chat interfaces is only one part of the picture. In this upcoming webinar, w...

Marathon Man II: how to pace a marathon *[April 11, 2026]: 2026-04-11T07:34:00+1000

R-bloggers

It’s often the way. I posted recently about how to pace a marathon and very quickly received feedback that would’ve improved the original post. Oh well, no going back. This is take two. So, we have a ...

Do AI coding agents save scientists time? *[April 11, 2026]: 2026-04-11T07:34:00+1000

R-bloggers

I’m often asked if using AI coding agents saves time. Yes they write code very quickly and can complete entire ecological data analyses. Do agents really help when the deadlines are approaching? Do ag...

reviser: Analyzing Real-Time Data Revisions in R *[April 11, 2026]: 2026-04-11T07:34:00+1000

R-bloggers

Economic data are rarely static. Gross domestic product (GDP), inflation, employment, and other official statistics arrive as early estimates, then get revised as new source data arrive, seasonal adju...