R

I have a draft chapter on Bayes stats and MCMC at https://oliviergimenez.github.io/banana-book/crashcourse.html I’d love your feedback about what is confusing and what is missing 😇 #rstats

So, I’m writing a book 🤯 It''’s called “Bayesian analysis of capture-recapture data with hidden Markov models - Theory and case studies in R”.

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.

Workshop to come on reproducible science in our lab.

Gathered some code on occupancy, capture-recapture & epidemiological models, social networks, spatial stuff, textual analyses, reproducible science, etc…

Developing, communicating and teaching methods and models for ecology and conservation biology.

Interactive data visualisation of bias in occupancy models w/ flexdashboard.

👩 💻🗺️👨 💻 The slides of my introduction to #GIS and #mapping in #rstats using the #sf 📦 and brown 🐻 distribution in the #pyrenees as a case study https://t.co/SKQOCzbxHn - raw material on #github https://t.

Procrastination at its highest level 😜 My first attempt to design hex stickers for our #R2ucare 📦 https://t.co/ZbclwJKB5W #rstats code on #github https://t.co/TbEgjQf7iC Comments more than welcome 😁 pic.twitter.com/vVdVnJ9B79 — Olivier Gimenez 🖖 (@oaggimenez) 6 février 2019