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

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樓主: Remodeling
51#
發(fā)表于 2025-3-30 09:03:37 | 只看該作者
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發(fā)表于 2025-3-30 13:26:55 | 只看該作者
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發(fā)表于 2025-3-30 16:47:43 | 只看該作者
I-Fang Lee,Chao-Ling Tseng,Hong-Ju June, (... ?), where .. are continuous random variates. In the first part we will focus our presentation on stationary Gaussian processes. These are most widely used in the analysis of, e.g., economic series or in signal processing.
54#
發(fā)表于 2025-3-30 20:56:36 | 只看該作者
Introduction and Historical Perspectivepractical point of view limited to small dimensions up to at most 10. And there are lots of distributions that are even difficult to sample from in dimension three or four. A totally different approach is based on the fact that we always can easily construct a Markov chain that has the desired fixed
55#
發(fā)表于 2025-3-31 01:54:47 | 只看該作者
https://doi.org/10.1007/978-3-662-05946-3Markov Chain; Monte Carlo Methods; Non-Uniform Random Variate; Option Pricing; Random Variate Generation
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發(fā)表于 2025-3-31 05:28:15 | 只看該作者
57#
發(fā)表于 2025-3-31 11:11:47 | 只看該作者
General Principles in Random Variate Generation of universal algorithms. Most of these methods can also be used for discrete distributions which will be presented in Chap. 3. These methods can also be used as starting points for compiling algorithms to generate random vectors, which will be done in Chap. 11.
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