Testing Legacy Shiny Apps: Start with Behavior, Not Code
Adding acceptance tests first makes refactoring safer. [Read more...]
R Package Quality: Maintainer Criteria
This is final part of a five part series of related posts on validating R packages.
Other posts in the series are:
Validation Guidelines
Package Popularity
Package Documentation
Code Quality
Maintenance (this post)
At last we come to the final ...
Repost: Tidy RAG in R with ragnar
Reposted from the original at: https://blog.stephenturner.us/p/tidy-rag-in-r-with-ragnarRetrieval augmented generation in R using the ragnar package. Demonstration: scraping text from relevant links on a website and using RAG to ask about a unive...
With help from LLMs (e.g. Deepseek) ! an R function that filters a list of vectors using indices from the unlisted data
Upon users' query, language learning models like ChatGPT and Deepseek can generate useful programming codes having been trained on many codes and texts available on the Internet. However, at least according to my experience the generated sc...
From Model to Meaning: How to use the marginaleffects R package to interpret results from statistical or machine learning models workshop
Join our workshop on From Model to Meaning: How to use the marginaleffects R package to interpret results from statistical or machine learning models, which is a part of our workshops for Ukraine series! Here’s some more info: Title: From Model to Meaning: How to use the marginaleffects R ... [Read more...]
Nested Forecasting: Analyzing the Relationship Between the Dollar and Stock Market Trends
The prevailing opinion is that because countries are exporting more goods to the US than it exports to them, resulting in a trade deficit. In return for their exports, these countries receive US dollars, which they often use to purchase US government bonds and stocks. Over time, this process contributes ...
Benchmarking memory usage in R
Benchmarking memory usage in R
Profiling memory in R has never been a trivial task.
In this post, I would like to emphasize that currently popular methods are quite inaccurate and should therefore be used with caution. More importantly, they sh...
What We Learned from Our First Data Science for Open WASH Data Course
A Global Response to a Critical Need 🌍
When we launched the first Data Science for Open WASH Data (ds4owd) course in October 2023, 235 WASH professionals from 46 countries around the world signed up—validating our belief that this community is ...
A modern introduction to probability and statistics [book review]
In the plane to Bengaluru, I read through the book A modern introduction to probability and statistics, by Graham Upton—whose Measuring Animal Abundance I reviewed for CHANCE a while ago—, which is based on the earlier Understanding Statistics, written jointly with Ian Cook. (Not to be confused with A ...
Apply the Dracula Theme to Quarto Websites
I am something of a Dracula theme fanatic. After first discovering the open-source theme in RStudio, I had to see if it was supported by other applications. To my delight, I found custom Dracula themes for over 400 applications. Applying these th... [Read more...]
Standard Deviation vs. Standard Error: Meaning, Misuse, and the Math Behind the Confusion
The left side illustrates standard deviation as the spread of individual data values around the population mean (μ). The right side shows standard error as the variability in sample means (x̄) obtained from repeated sampling. Notice how the ...
Exploring R and Rust in Bioinformatics – Online Developer Forum, 28 July 2025
Join us for an open developer forum exploring how R and Rust can work together in bioinformatics and Bioconductor development. Organised and hosted by Lluís Revilla (Bioconductor Community Advisory Board), this online session will discuss techn...
How to choose an IDE
When it comes to choosing an IDE to install there are lots of different choices out there, each with different pros and cons. This blog post isn’t about recommending or endorsing any specific IDE, but more about what questions you might want to a...
R Package Quality: Code Quality
This is part four of a five part series of related posts on validating R packages.
Other posts in the series are:
Validation Guidelines
Package Popularity
Package Documentation
Code Quality (this post)
Maintenance
In this post, we’ll take...
Standard Deviation vs. Standard Error: Meaning, Misuse, and the Math Behind the Confusion
The left side illustrates standard deviation as the spread of individual data values around the population mean (μ). The right side shows standard error as the variability in sample means (x̄) obtained from repeated sampling. Notice how the S...
data.table is a NumFOCUS project!
We are SO excited to announce some massive news for the data.table community: data.table is now a NumFOCUS Sponsored Project!!!
For those who aren’t familiar, NumFOCUS is an incredible nonprofit organization that supports open source projects....
Monads everywhR
A monad is a very useful pattern. If you don’t know what it is, then read my
post from a few years ago, watch
this excellent video, and
you can also read J. Carroll’s insightful
post. Once you think you get
the concept, this blog post will ... [Read more...]
Bioconductor’s First Microbiome Course in Brazil: A Successful Workshop at UFMG in Belo Horizonte
From April 23rd to 25th, 2025, we hosted the first Bioconductor microbiome course in Brazil, a three-afternoon workshop held at the Interunits Post-Graduate Program of Bioinformatics at the Federal University of Minas Gerais (UFMG) (link) i...
Paradoxes in Credit Risk II: The Through-the-Door Problem
In this post, I want to describe one of the most important aspects of credit risk modelling and explain how it also comes up in many other fields.
Previous posts in this series: Paradoxes in Credit Risk I: Simpson’s Paradox
What is the through-the-do...
Perform a Likelihood Ratio Test in R
You've built two regression models—one simple and one more complex model. The complex one seems to have a slightly better fit, but is that improvement statistically meaningful, or just noise from the observed data? How do you prove, with statistical certainty, that the extra complexity is actually worth it?
... [Read more...]
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