Titlebook: Automatic Nonuniform Random Variate Generation; Wolfgang Hörmann,Josef Leydold,Gerhard Derflinger Book 2004 Springer-Verlag Berlin Heidelb

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Combination of Generation and Modelingt have the “same property” as the observed sample. Strictly speaking questions of this kind are not the subject of a book dealing with random variate generation. But due to its great practical importance we decided to include this chapter.

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Book 2004andom 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 co

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General Principles for Discrete Distributionshe inversion (Sect. 3.1) and the rejection principle (Sect. 3.3) that are also of major importance for continuous distributions. We also present the alias method (Sect. 3.2) which was developed especially for discrete distributions.

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Comparison and General Considerationshich can be downloaded from our web site as C source, see Sect. 8.1. It is not only a ready to use implementation of these algorithms, it is also a detailed reference of how these algorithms can be implemented in a programming language.

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Globalization and Health Promotionf these methods. We give an overview and present the details of those algorithms that seem to be most useful in practice; among them a new automatic algorithm for distributions with increasing hazard rate.