I had to use the good old `OpenBUGS` for some analyses that cannot be done in `JAGS`. Below are the steps to install `OpenBUGS` then to run it from your Mac either natively or from `R`. This tutorial is an adaptation of [this post](https://sites.google.com/site/mmeclimate/-bayesmet/openbugs-on-mac-os-x) and [that one](http://www.davideagle.org/r-2/bayesian-modeling-using-winbugs-and-openbugs/running-openbugs-on-mac-using-wine).

Our project `Avoid, reduce and compensate mortality risks of the Eurasian Lynx by collision with transport vehicles` aims to build on previous works on lynx population viability, collision risks while crossing terrestrial transport infrastructures and mitigation strategies. Our team will develop an operational tool upon which the technical operators will be able to rely on in the decision-making process for land-use planning. More details [here](https://sites.google.com/view/erclynx/) (in French).

Here, I illustrate the possibility to use `JAGS` to simulate data with two examples that might be of interest to population ecologists: first a linear regression, second a Cormack-Jolly-Seber capture-recapture model to estimate animal survival (formulated as a state-space model). The code is available from [GitHub](https://github.com/oliviergimenez/simul_with_jags).

Following my recent attempt to [fit a HMM model to capture-recapture data with TMB](https://oliviergimenez.github.io/post/multievent_in_tmb/) and the rather estonishing outcome (the code was > 300 time faster than the equivalent R code!), I was curious to add TMB to the [list of options I tried to fit dynamic occupancy models](https://oliviergimenez.github.io/post/occupancy_in_admb/). Well, the least I can say is that TMB is fast, damn fast!

Following my attempts to fit a HMM model to [capture-recapture data with Rcpp](http://localhost:1313/post/multievent_in_rcpp/) and to [occupancy data with ADMB](http://localhost:1313/post/occupancy_in_admb/), a few colleagues suggested TMB as a potential alternative for several reasons (fast, allows for parallel computations, works with R, accomodates spatial stuff, easy implementation of random effects, and probably other reasons that I don't know).

Over the years (age privilege), I sat on several hiring committees for French universities and research institutes. I also have students who are now in the position to apply for such positions. It had me thinking about what works and what doesn't work in job applications and interviews. Here are my 2 cents suggestions.

Following my previous post on [using ADMB to fit hidden Markov models](https://oliviergimenez.github.io/post/occupancy_in_admb/), I took some time to learn how to use Rcpp ([Eddelbuettel & Francois 2011](https://www.jstatsoft.org/article/view/v040i08); [Eddelbuettel 2013](http://www.springer.com/us/book/9781461468677)), a package that gives friendly access to the power of C++ and increase the speed of your R programs. Kudos to Dirk Eddelbuettel, Romain Francois and their colleagues, Rcpp is awesome!

Some time ago, a student of mine got stuck when fitting dynamic occupancy models to real data in Jags because of the computational burden.

I just submitted to Oikos a paper entitled "Individual heterogeneity and capture-recapture models: what, why and how?". A pre-print is available [here](http://biorxiv.org/content/early/2017/03/26/120683). I also provide R codes on GitHub [there](http://bit.ly/2nqWzoZ).

Our report (in French) on foresighting wolf population dynamic in France is available from [here](https://t.co/a6ibQoF7Nr). My contribution was mostly based on the work of my present or former students, including L. Marescot, J. Louvrier and S. Cubaynes.