Fast conformal prediction (no refitting) for some Machine Learning models via closed-form jackknife plus
Fast conformal prediction for some Machine Learning models via closed-form jackknife plus (no refitting involved, just Linear Algebra).
stick function for the EDA in time series
You have probably seen my post about the STI classification of Hans Levenbach (this one). Well, I’ve decided to implement it, and it has landed in the greybox package for R/Python. What’s greybox? It is a package for statistical modelling focusing on forecasting and time series analysis. ... [Read more...]
AI in Production Conference Summary (2026)
“AI In Production 2026”, a new conference hosted
by Jumping Rivers, was held on 4-5 June, 2026. The conference touched on many of the intricacies of
using AI in software products, as part of the developer toolkit, and at the wider us...
SIM2 climate data
Temperature change in France – CC-BY by University of Reading
As France enters its second heatwave of 2026, can we produce more detailed plots than the excellent visualizations provided by ShowYourStripes?
MétéoFrance offers its monthly SI...
Winter R workshops at University of Queensland, Brisbane
My colleagues run some highly regarded R workshops for well over a decade in Brisbane (Australia) every year.
Details here and info below
Are you ready to take your R skills to the next level and conquer the challenges of messy data? Transform r... [Read more...]
Data for fitting models versus data for predicting from models
Answering a question that came up from a student recently.
Say you have 20 surveys of reef fish biomass at different locations. Then you also have gridded data with environmental covariates. The gridded data is for all reefs everywhere.
The goal... [Read more...]
Set Working Directory in R: setwd() & RStudio GUI Guide
Learn how to set your working directory in R using setwd() or the RStudio Session menu. Covers getwd(), Windows path errors, and the here() package for dissertation projects.
Read More » [Read more...]
Introduction to Bayesian Multiple Imputation with the rblimp package workshop
Join our workshop on Introduction to Bayesian Multiple Imputation with the rblimp package, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Introduction to Bayesian Multiple Imputation with the rblimp package Date: Thursday, July 23rd, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) Speaker: Ermioni Athanasiadi ... [Read more...]
Flowcharts that belong in the analysis pipeline
Thanks to Alan Haynes and his excellent suggestions, I have spent some time improving the flowchart component of the Gmisc package. The result is not meant to be another decorative diagram tool. It is meant for the kind of figures … Continue reading →
EFA vs CFA: Key Differences Between Exploratory & Confirmatory Factor Analysis (R)
EFA explores unknown factor structures while CFA tests a predefined model. Compare both methods side by side with R code using psych and lavaan — know which to use in your dissertation.
EFAEFA explores unknown factor structures while CFA tests a predefined model. Compare both methods side by side with R ...
United Kingdom prime ministers by @ellis2013nz
With the recent resignation announcement from United Kingdom (UK) Prime Minister Keir Starmer, there have been a flurry of people talking about how many UK prime ministers there have been in the past decade, short terms for prime ministers, and so on. ...
Using scikit-learn models in R easily with the tisthemachinelearner package
Using the tisthemachinelearner R package to train scikit-learn models and compute prediction intervals
PCA in R: Principal Component Analysis Step-by-Step (prcomp + ggplot2)
How to Perform PCA in R: A Step-by-Step Tutorial Using prcomp()
To perform PCA in R, use the built-in prcomp() function: pca 1), or a cumulative variance threshold — this tutorial shows all three and where they disagree.
PCA is not the same as Factor Analysis. The comparison table below explains exactly ...
Celebrating Our Maintainers during Maintainers Month
May was Open Source Software Maintainer Month.
Behind every R package there is at least one person who responds to issues, reviews pull requests, keeps up with dependency changes, and makes sure everything still works.
During Maintainer Month we wante... [Read more...]
EuroBioC2026 conference recap
The European Bioconductor Conference 2026 (EuroBioC2026) took place from June 3-5, 2026, in Turku, Finland. Hosted by the University of Turku and the Finnish Society for Bioinformatics at BioCity, the conference brought together the Bioconducto...
Mistral AI : Le Mirage du SaaS et le Grand Pivot vers le Réel
Le 16 juin 2026, Arthur Mensch, le patron emblématique de Mistral AI, a publié sur LinkedIn un message d’une rare solennité. Le discours officiel y célèbre, comme toujours, l’indépendance technologiqu [Read more...]
Likert Scale Questions: Your In-Depth Guide
A Likert scale (pronounced LICK-ert, not "LIKE-ert") is a psychometric rating scale used in surveys and questionnaires to measure attitudes, opinions, and perceptions. Named after American social psychologist Rensis Likert, who developed it in 1932, it remains the most widely used approach to scaling responses in survey research today.
Key Takeaways
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2026 Rousseeuw Prize for Statistics Awarded to R Core Team for Transforming Statistics Computing Worldwide
The Rousseeuw Prize honors five pioneering developers for nearly three decades of unpaid work building R, the foundational open-source computing language behind artificial intelligence, healthcare, and economic decision-making. The $1 million Rousseeuw Prize for Statistics recognizes three decades of foundational work that transformed how statistical methods are developed, validated, and shared ... [Read more...]
{talib}: Interactive financial charts
{talib} is a new R package built on TA-Lib, which is now available on CRAN. The R-package is targeted at individuals and, perhaps, institutions who, in some form or the other, interacts with the financial markets using technical analysis. The library is built with minimal dependencies for long-term stability and ...
Announcing shiny.webawesome: a web UI package for R/Shiny
shiny.webawesome brings Web Awesome to R Shiny through generated wrappers, reactive bindings, and a bundled runtime. It aims for complete component support while staying close enough to upstream that the Web Awesome docs and examples are directly useful in everyday package use. CRAN | R-universe | Package website | Source repository Background ... [Read more...]
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