A (hopefully) gentle intro to JAGS, NIMBLE and linear regression of continuous variables. 

A continuation of Part 1 featuring  categorical variables, model selection with DIC and WAIC, and graphing credible intervals.  

Gotta love 'em, right? An overview of some of the more common error messages and why they arise. 

An introduction to occupancy modeling in a Bayesian framework with both site and detection covariates.

An introduction to writing a Metropolis- Hastings MCMC sampler for very simple distributions. 

An overview of indicator variable selection - a type of Bayesian model selection combined with model averaging 

A very light overview to choosing initial values for JAGS models in R.

 Closed N-mixture models with binomial, double observer, and removal sampling detection in both JAGS and NIMBLE

 Dynamic N-mixture models in JAGS and NIMBLE, plus some helpful code for choosing initial values. 

 Known Fate models in JAGS and NIMBLE, plus survival curve graphs

 Some examples of Distance Sampling in JAGS and NIMBLE - line transects, point count surveys and hierarchical distance sampling

A quick tutorial on how to get started with R Markdown.