We had to dig out some #rstats #jags code to fit a structural equation capture-recapture model we developed w/ @SCubi25 in a 8-year old @ESAEcology paper (!), and it runs like a charm 🥳🍾#reproducibility ➡️ https://t.
🇬🇷🐬📈@NSantostasi shows in her new paper https://t.co/EZIvJFZbV1 that Common dolphins in the Gulf of Corinth are Critically Endangered (w/ a stochastic PVA) #WomenInSTEM @IUCNRedList #FreeAccess 🇫🇷🇮🇹 pic.twitter.com/eC0plbVgeW
— Olivier Gimenez 🖖 (@oaggimenez) February 2020
New @biorxivpreprint #preprint led by Sarah Bauduin 🐺💻 From ind behavior and pack dynamics to pop responses: An #IBM to model #wolf social life cycle https://t.co/ea31RvDMoE w/ contributions by @NSantostasi & @oksanagrente #rstats code ➡️ https://t.
Happy 2020 #rstats! To celebrate, my modest first #TidyTuesday submission for wk 2019-52. Spatio-temporal trends in 🐺 presence in 🇫🇷 w/ data from @oncfs @OFBiodiversite (bugged dynamic map below)#ggplot2 #tidyverse #dataviz #sf @thomas_mock Code: https://t.
In statistical ecology, we often need to calculate the sampling variance of a function of an estimate of which we do know the sampling variance. I keep forgetting how to implement the so-called delta method in R that allows to get an approximation of this quantity. So in this post I go through two examples in population ecology that should help me remembering. I use the deltamethod function from the msm package.
I read this awesome post (in French) by Baptiste Coulmont, professor in sociology, who explored the French academic network in sociology. Coulmont used the composition of PhD commitees to determine academic links between colleagues. The approach very appealing because it uses public data available from the website these.fr. Here, I used Coulmont’s R code to produce the French academic network in ecology. This was a nice opportunity to illustrate how to work in the tidyverse and to do some web scraping using the rvest package.
🐬🇬🇷🇮🇹🇫🇷 New paper by @NSantostasi @INEE_CNRS @CNRS_OccitaniE @IsiteMUSE @umontpellier 🤩👏 https://t.co/6vQ6d9HevV
— Olivier Gimenez 💤 (@oaggimenez) 9 novembre 2018
#INLA workshop on spatio-temporal models in the beautiful city of #Avignon 🤩 #RESSTE #GdREcoStat @oksanagrente @CREEM_cake pic.twitter.com/nuLhIkMiwO
— Olivier Gimenez 💤 (@oaggimenez) 718
The famous #NetLogo butterfly example coded in #rstats w/ #NetLogoR pic.twitter.com/VbUUa5vIep
— Olivier Gimenez 🚸 (@oaggimenez) 5 novembre 2018 Wolf model from Marucco & @eliotmcintire coded in #rstats w/ #NetLogoR & #SpaDES https://t.
Recently, I have been using `OpenBUGS` for some analyses that `JAGS` cannot do. However, `JAGS` can be run in parallel through [the `jagsUI` package](https://github.com/kenkellner/jagsUI), which can save you some precious time. So the question is how to run several chains in parallel with `OpenBUGS`.