Introducing Monte Carlo Methods with R

This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

Table of Contents

Chapter 1 Basic R Programming
Chapter 2 Random Variable Generation
Chapter 3 Monte Carlo Integration
Chapter 4 Controlling and Accelerating Convergence
Chapter 5 Monte Carlo Optimization
Chapter 6 Metropolis–Hastings Algorithms
Chapter 7 Gibbs Samplers
Chapter 8 Convergence Monitoring and Adaptation for MCMC Algorithms