Lecture notes on Monte Carlo statistical methods by Christian P. Robert -364 pages-

Lecture notes on Computational Statistics by Zhenli Xu -99 pages-

Lecture notes on Computer intensive methods by Omiros Papaspiliopoulos -63 pages-

Lecture notes on Fundamentals of Statistical Inference by Gareth Roberts -61 pages-

Bootstrap methods and permutation tests by Tim Hesterberg, Shaun Monaghan, David S. Moore, Ashley Clipson and Rachel Epstein -85 pages-

Bootstrap methods in econometrics by James G. MacKinnon -50 pages-

Discrete Choice Methods with Simulation by Kenneth Train -ziped file with all chapters in pdf format-

Advanced Statistical Computing -lecture notes by Robert Gray -329 pages-

"Resampling: The New Statistics" by Julian L. Simon (on-line textbook)

The Bootstrap and Edgeworth Expansion by Peter Hall - 368 pages -

Computational Methods in Statistics by Eric Slud

Brief notes on Sampling Methods by Agner Fog -5 pages-

Bootstrap Estimation by Kenneth J. Koehler -26 slides-

David C. Howell's Resampling statistics: randomization and the bootstrap

Lecture notes on Computational statistics by Maria Kateri -141 slides in Greek-

Simulation Methods

Lecture notes on Simulation and stochastic models by Petros Dellaportas -61 pages in Greek-

Simulation techniques and compuational statistical techniques by Michael Boutsikas -course webpage in Greek-

Lecture notes on Rejection Sampling by Dimitris Fouskakis -11 slides in greek-

Monte Carlo Integration Method

Basics of Monte Carlo Simulations by Kai Nordlund -course webpage-

History of Monte Carlo Method by Sabri Pllana -on line book-

Lecture notes on Monte Carlo integration by Kristopher R. Beevers -8 pages-

MCMC Algorithm

Bayesian Modeling in the Social Sciences: an Introduction to MCMC -lecture notes by Simon Jackman -120 pages-

Probability and MCMC by Jeffrey S. Rosenthal -50 pages-

MCMC Preprint Service

The EM Algorithm

Lecture Notes on the EM Algorithm by Mario A. T. Figueiredo -35 pages-

The Expectation Maximization algorithm, intuitive explanation by Frank Dellaert -7 pages-

The Expectation Maximization Algorithm A short tutorial by Sean Borman -9 pages-

The Expectation - Maximization Algorithm by Tood K. Moon -14 pages-

EM Examples by Kenneth Lange -28 slides-

Acceptance sampling by Metin Çakanyildirim -55 slides-

Acceptance sampling by the University of Plymputh -22 pages-

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