| Description |
xxi, 507 pages |
| Series |
Springer texts in statistics |
|
Springer texts in statistics.
|
| Contents |
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 -- A. Probability Distributions -- B. Notation |
| Summary |
"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."--BOOK JACKET |
| Bibliography |
Includes bibliographical references (page -) and index |
| Subject |
Mathematical statistics.
|
|
Monte Carlo method.
|
| Author |
Casella, George.
|
| LC no. |
98055413 |
| ISBN |
038798707X alkaline paper |
|
