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An introduction to statistical computing : a simulation-based approach / Jochen Voss

By: Voss, Jochen.
Material type: TextTextSeries: Wiley series in computational statistics.Publisher: Chichester, West Sussex : Wiley, 2014Description: xii, 382 pages : illustrations ; 24 cm.ISBN: 9781118357729 (hardback); 1118357728 (hardback).Subject(s): Mathematical statistics -- Data processing | MATHEMATICS / Probability & Statistics / GeneralDDC classification: 519.50113 Online resources: WorldCat details | E-book Fulltext
Contents:
Table of contents Pseudo random number generators -- 1.1.1. 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.
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"--
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Non-fiction 519.50113 VOI 2014 (Browse shelf) Not for loan
Text Text EWU Library
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Includes bibliographical references (pages 375-377) and index.

Table of contents Pseudo random number generators --
1.1.1. 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.

"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"--

Applied Statistics

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