Synopsis
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 Hörmann).- 14 Markov Chain Monte Carlo Methods.- 15 Some Simulation Examples.- List of Algorithms.- References.- Author index.- Selected Notation.- Subject Index and Glossary.
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