{"product_id":"9781461373797","title":"International Series in Operations Research \u0026 Management Science","description":"\u003ch1\u003eInternational Series in Operations Research \u0026amp; Management Science\u003c\/h1\u003e \u003ch2\u003eFox, Bennett L.\u003c\/h2\u003e \u003cp\u003e\u003cem\u003eStrategies for Quasi-Monte Carlo\u003c\/em\u003e builds a framework to  design and analyze strategies for randomized quasi-Monte Carlo (RQMC).  One key to efficient simulation using RQMC is to structure problems to  reveal a small set of important variables, their number being the  effective dimension, while the other variables collectively are  relatively insignificant. Another is smoothing. The book provides many  illustrations of both keys, in particular for problems involving  Poisson processes or Gaussian processes. RQMC beats grids by a huge  margin. With low effective dimension, RQMC is an order-of-magnitude  more efficient than standard Monte Carlo. With, in addition, certain  smoothness - perhaps induced - RQMC is an  order-of-magnitude more efficient than deterministic QMC. Unlike the  latter, RQMC permits error estimation via the central limit theorem.  For random-dimensional problems, such as occur with discrete-event  simulation, RQMC gets judiciously combined with standard Monte Carlo  to keep memory requirements bounded. \u003cbr\u003e  This monograph has been designed to appeal to a diverse audience,  including those with applications in queueing, operations research,  computational finance, mathematical programming, partial differential  equations (both deterministic and stochastic), and particle transport,  as well as to probabilists and statisticians wanting to know how to  apply effectively a powerful tool, and to those interested in  numerical integration or optimization in their own right. It  recognizes that the heart of practical application is algorithms, so  pseudocodes appear throughout the book. While not primarily a  textbook, it is suitable as a supplementary text for certain graduate  courses. As a reference, it belongs on the shelf of everyone with a  serious interest in improving simulation efficiency. Moreover, it will  be a valuable reference to all those individuals interested in  improving simulation efficiency with more than incremental increases.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2012-10-12\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9781461373797\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4615-5221-5\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 368\u003c\/p\u003e ","brand":"Springer US","offers":[{"title":"Default Title","offer_id":44358922010764,"sku":"9781461373797","price":152.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781461373797.jpg?v=1775004659","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781461373797","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}