MCMC

1) Computational Statistics with Matlab (by Mark Steyvers)

2) Gibbs sampler tutorial (by Jun Liu)

3) Multiscale MCMC code (R code)

4) Parallel MCMC

5) Running MCMC chains in parallel

6) Basic linear algebra, MCMC and Gibbs sampling (CS 530 UNM, Prof. Joe Kniss)

7) MCMC tutorial (Tutorial Lectures on MCMC I by Sujit Sahu University of Southampton)

8) MATLAB code for Metropolis-Hastings with burn-in and lag (COMPSCI 3016: Computational Cognitive Science by Dan Navarro & Amy Perfors, University of Adelaide)

9) Blog on metropolis-hastings

10) Gibbs sampling (wikipedia)

11) Wishart distribution (utility)

12) MCMC implementations in R, Python, Java and C (by Darren Wilkinson)

13) Adaptive MCMC (Optimal Proposal Distributions and Adaptive MCMC by Jeffrey Rosenthal link)

14) Book on Markov Chains and Mixing Times (by David Levin, Yuval Peres and Elizabeth Wilmer link and here)

15) Book Mathematical Aspects of Mixing Times in Markov Chains (by Montenegro and Tetali here and here)

16) Best book - Markov Chain Monte Carlo in Practice (by Gilks, Richardson and Spiegelhalter)