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Welcome 👋 :bowtie: My name is Olivier Gimenez and I am a 🇫🇷 researcher working at the interface of animal ecology 🐺 🐬 🐘, statistical modeling 📉 and social sciences 📚.

On my GitHub, you will find repos with research and teaching material you can use for your own purpose. Check out also these Gists (short bits of code and data).

For more info, check out oliviergimenez.github.io or reach out on Twitter.

Olivier Gimenez's Projects

multistate_recaprecov icon multistate_recaprecov

Some R/Jags code to demonstrate an issue with local max in the likelihood when fitting multistate capture-recapture models

my_website icon my_website

Source code of my website https://oliviergimenez.github.io/.

netdem-workshop-survival-nimble icon netdem-workshop-survival-nimble

This repository holds the source materials used for a working group/symposium on capture-recapture models and social networks, and an introduction to capture-recapture models in nimble to estimate demographic parameters.

neuralecology icon neuralecology

Code for the paper "Neural hierarchical models of ecological populations"

nimble icon nimble

A repository to test and learn NIMBLE

occupancy_in_admb icon occupancy_in_admb

Illustrate how to fit dynamic occupancy model in ADMB. Benchmarking with Unmarked and JAGS.

occupancy_tmb icon occupancy_tmb

Illustrate how to fit dynamic occupancy model in TMB. Benchmarking vs. ADMB, Unmarked and JAGS.

oliviergimenez.github.io icon oliviergimenez.github.io

My site, built with Hugo and Blogdown, and hosted on Github pages. Built and deployed with GitHub Actions from https://github.com/oliviergimenez/my_website repo.

p2cr icon p2cr

Fit principal component capture-recapture model to snow petrel data

poaching_occupancy icon poaching_occupancy

Inferring poaching with multispecies dynamic occupancy models and hidden Markov models

popdyn-workshop icon popdyn-workshop

Website of workshop Quantitative Methods for Population Dynamics in R

power_analysis_interaction_networks icon power_analysis_interaction_networks

This repository contains code to compute the correlation between an estimated social network and the true, unobserved social network for networks constructed from interaction rates.

presidentielle22 icon presidentielle22

Analyse des résultats de la présidentielle 2022 par bureau de vote à Montpelier

prezdloccupancy icon prezdloccupancy

Slides of a talk on deep learning, false negatives/positives and predator-prey interactions with R.

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