Author	Hรถrmann, Wolfgang. author
Title	Automatic Nonuniform Random Variate Generation [electronic resource] / by Wolfgang Hรถrmann, Josef Leydold, Gerhard Derflinger
Imprint	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004
Connect to	http://dx.doi.org/10.1007/978-3-662-05946-3
Descript	X, 441 p. 89 illus. online resource

Non-uniform random variate generation is an established research area in the intersection of mathematics, statistics and computer science. Although random variate generation with popular standard distributions have become part of every course on discrete event simulation and on Monte Carlo methods, the recent concept of universal (also called automatic or black-box) random variate generation can only be found dispersed in literature. This new concept has great practical advantages that are little known to most simulation practitioners. Being unique in its overall organization the book covers not only the mathematical and statistical theory, but also deals with the implementation of such methods. All algorithms introduced in the book are designed for practical use in simulation and have been coded and made available by the authors. Examples of possible applications of the presented algorithms (including option pricing, VaR and Bayesian statistics) are presented at the end of the book

1 Introduction -- 2 General Principles in Random Variate Generation -- 3 General Principles for Discrete Distributions -- 4 Transformed Density Rejection (TDR) -- 5 Strip Methods -- 6 Methods Based on General Inequalities -- 7 Numerical Inversion -- 8 Comparison and General Considerations -- 9 Distributions Where the Density Is Not Known Explicitly -- 10 Discrete Distributions -- 11 Multivariate Distributions -- 12 Combination of Generation and Modeling -- 13 Time Series (Authors Michael Hauser and Wolfgang Hรถrmann) -- 14 Markov Chain Monte Carlo Methods -- 15 Some Simulation Examples -- List of Algorithms -- References -- Author index -- Selected Notation -- Subject Index and Glossary

1. Mathematics
2. Computer science -- Mathematics
3. Computer simulation
4. Computer mathematics
5. Algorithms
6. Probabilities
7. Statistics
8. Mathematics
9. Computational Mathematics and Numerical Analysis
10. Probability Theory and Stochastic Processes
11. Mathematics of Computing
12. Statistics and Computing/Statistics Programs
13. Algorithms
14. Simulation and Modeling