Rstats

I would like to familiarize myself with machine learning (ML) techniques in R. So I have been reading and learning by doing. I thought I’d share my experience for others who’d like to give it a try1.

I use R to retrieve some data from Twitter, do some exploratory data analysis and visualisation and examine a network of followers.

Slides and codes available from https://sarahbauduin.github.io/formation_IBM_NetLogoR/.

Everything (including data, slides, codes and video recordings) about the workshop we run on Bayesian capture-recapture inference with hidden Markov models in R and Nimble.

Everything (including data, slides and codes) about the workshop on Bayesian statistics I run.

Everything (including data, slides and codes) about the workshop on reproducible science I run.

Bayesian implementation of Pollock’s robust design capture-recapture models w/ Jags.

In our weekly group meeting this morning, I introduced R Markdown a great #rstats tool to write reproducible documents (reports, articles, slides, websites) smoothly mixing text, code, figures and equations in html, word or pdf format.

In a recent seminar, S. Gandon (w/ S. Lion and T. Day) used SIR models to illustrate the effect of diff strategies of #SocialDistancing on the #COVID19 epidemic. What better way to learn than to reproduce their results in R? My two cents #rstats code ➡️ https://t.co/oJVQHJ6HqO 🤓 pic.twitter.com/dqSIcjbhqq

It is my pleasure to announce that Michael Schaub and Marc Kéry will run their Integrated Population Modelling workshop in Montpellier this November.