An introduction to statistical computing: a simulation-based approach
by Voss, Jochen
"This is a book about exploring random systems using computer simulation and thus, this book combines two different topic areas which have always fascinated me: the mathematical theory of probability and the art of programming computers"
Read More ↓Title Statements
- Full title :An introduction to statistical computing : a simulation-based approach / Jochen Voss
Summary
"This is a book about exploring random systems using computer simulation and thus, this book combines two different topic areas which have always fascinated me: the mathematical theory of probability and the art of programming computers"
Read More ↓Edition Statements
- Publication Date:c 2014 [erschienen 2013]
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Chichester
- Language:eng
- Publication Date:c 2014 [erschienen 2013]
The Physical Object
- Description:XII, 382 Seiten : Illustrationen, Diagramme
Edition Identifiers
- ISBN:9781118357729, 1118357728, 9781118728024, 1118728025
- oclc:ocn931239115
- LC Classification:QA276.4
- Dewey Decimal:519.501/13
Table of Contents
Pseudo random number generators1.1.1. The linear congruential generator -- 1.1.2. Quality of pseudo random number generators -- 1.1.3. Pseudo random number generators in practice -- 1.2. Discrete distributions -- 1.3. The inverse transform method -- 1.4. Rejection sampling -- 1.4.1. Basic rejection sampling -- 1.4.2. Envelope rejection sampling -- 1.4.3. Conditional distributions -- 1.4.4. Geometric interpretation -- 1.5. Transformation of random variables -- 1.6. Special-purpose methods -- 1.7. Summary and further reading -- Exercises -- 2. Simulating statistical models -- 2.1. Multivariate normal distributions -- 2.2. Hierarchical models -- 2.3. Markov chains -- 2.3.1. Discrete state space -- 2.3.2. Continuous state space -- 2.4. Poisson processes -- 2.5. Summary and further reading -- Exercises -- 3. Monte Carlo methods -- 3.1. Studying models via simulation -- 3.2. Monte Carlo estimates -- 3.2.1.Computing Monte Carlo estimates.
Note continued: 3.2.2. Monte Carlo error3.2.3. Choice of sample size -- 3.2.4. Refined error bounds -- 3.3. Variance reduction methods -- 3.3.1. Importance sampling -- 3.3.2. Antithetic variables -- 3.3.3. Control variates -- 3.4. Applications to stati…
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