Monte Carlo Statistical Methods

Monte Carlo Statistical Methods, Particularly Those Based On Markov Chains, Have Now Matured To Be Part Of The Standard Set Of Techniques Used By Statisticians. Written As A Self-contained Logical Development Of The Subject, This Book Will Be Suitable As An Introduction To The Field Or As A Textbook Intended For A Second-year Graduate Course. The Reader Is Not Assumed To Have Any Familiarity With Monte Carlo Techniques (such As Random Variable Generation), Or With Any Markov Chain Theory.--jacket. 1. Introduction -- 2. Random Variable Generation -- 3. Monte Carlo Integration -- 4. Markov Chains -- 5. Monte Carlo Optimization -- 6. The Metropolis-hastings Algorithm -- 7. The Gibbs Sampler -- 8. Diagnosing Convergence -- 9. Implementation In Missing Data Models. Christian P. Robert, George Casella. Includes Bibliographical References (p.[459]-487) And Index.