| 书目名称 | Strategies for Quasi-Monte Carlo | | 编辑 | Bennett L. Fox | | 视频video | | | 丛书名称 | International Series in Operations Research & Management Science | | 图书封面 |  | | 描述 | .Strategies for Quasi-Monte Carlo. builds a framework todesign and analyze strategies for randomized quasi-Monte Carlo (RQMC).One key to efficient simulation using RQMC is to structure problems toreveal a small set of important variables, their number being theeffective dimension, while the other variables collectively arerelatively insignificant. Another is smoothing. The book provides manyillustrations of both keys, in particular for problems involvingPoisson processes or Gaussian processes. RQMC beats grids by a hugemargin. With low effective dimension, RQMC is an order-of-magnitudemore efficient than standard Monte Carlo. With, in addition, certainsmoothness - perhaps induced - RQMC is anorder-of-magnitude more efficient than deterministic QMC. Unlike thelatter, RQMC permits error estimation via the central limit theorem.For random-dimensional problems, such as occur with discrete-eventsimulation, RQMC gets judiciously combined with standard Monte Carloto keep memory requirements bounded. .This monograph has been designed to appeal to a diverse audience,including those with applications in queueing, operations research,computational finance, mathematical programming, partial di | | 出版日期 | Book 1999 | | 关键词 | Operations Research; Simulation; Variance; algorithms; analysis of variance; calculus; optimization; statis | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4615-5221-5 | | isbn_softcover | 978-1-4613-7379-7 | | isbn_ebook | 978-1-4615-5221-5Series ISSN 0884-8289 Series E-ISSN 2214-7934 | | issn_series | 0884-8289 | | copyright | Springer Science+Business Media New York 1999 |
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发表于 2025-3-21 16:07:50
