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. This book is intended to bring these techniques into the class room, being (we hope) a self-contained logical development of the subject,...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
1999, 1999
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| Edition: | 1st ed. 1999 |
| Series: | Springer Texts in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of 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
- B.1 Mathematical
- B.2 Probability
- B.3 Distributions
- B.4 Markov Chains
- B.5 Statistics
- B.6 Algorithms
- C References
- Author Index