This is a listing, by session, of all the R-code companions available for the SISG MCMC course, as well as a few other materials.

- Estimating probabilities in the Wright-Fisher model. We make a simple R function to simulate the Wright-Fisher model at a single biallelic locus, and then we approximate some \(t\)-step transition probabilities by Monte Carlo.
- Random Walk with Scattering Boundaries, and Limiting Distributions. We devise a simple 5-state Markov chain, explore its properties, simulate from it and observe the consequences of the Weak Law of Large numbers for ergodic chains.

- Session 3: Introduction to MCMC in R (Computing Practical). This is the session code in notebook format.

- MCMC Sampling for a Simple Inbreeding Model. We review our simple model for inbreeding at a locus and develop the code to perform several different types of Metropolis-Hastings updates, then augment the model to include latent variables that let us easily to Gibbs-sampling updates.

- Analyzing multiple runs of structure. Using a little R package,
`Rrunstruct`

, to conduct multiple structure runs, obtain trace information from the runs, and compare the results from multiple runs.

- You can get the
`cats.dat`

data set by clicking this link, and then copying the data and putting it into a text file on your computer named`cats.dat`

.

- Thermodynamic Integration
- Matthew Stephensâ€™ 5-minute Statistics Page
- Monte Carlo Methods and Importance Sampling. A short thing that Eric wrote when a grad student and substitute lecturing. This formed the basis for some of the material on vanilla Monte Carlo and Importance Sampling.

- SISG MCMC main GitHub repo. This has all the materials for the lecture notes, etc.
- GitHub Repo for Ericâ€™s OpenGL-based simulation visualizations. This is a bunch of code written in C.