Contents

• Introduction
• Markov Chains
  • Specification of the Model and Examples
  • Ergodicity and Stationarity
  • Reversibility; Estimates for the Rate of Convergence
• Monte-Carlo Simulation
  • Generation of Pseudo-Random Numbers
  • Transformation of Uniformly Distributed Random Numbers
  • Simulation Methods Based on Markov Chains
  • Error Analysis for MCMC Simulation
  • Coupling Algorithms; Perfect MCMC Simulation
• About this document ...