| 書目名稱 | Random Number Generation and Monte Carlo Methods |
| 編輯 | James E. Gentle |
| 視頻video | http://file.papertrans.cn/822/821062/821062.mp4 |
| 叢書名稱 | Statistics and Computing |
| 圖書封面 |  |
| 描述 | .Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These "pseudorandom" numbers must pass statistical tests just as random samples would. Methods for producing pseudorandom numbers and transforming those numbers to simulate samples from various distributions are among the most important topics in statistical computing. ..This book surveys techniques of random number generation and the use of random numbers in Monte Carlo simulation. The book covers basic principles, as well as newer methods such as parallel random number generation, nonlinear congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo. The best methods for generating random variates from the standard distributions are presented, but also general techniques useful in more complicated models and in novel settings are described. The emphasis throughout the book is on practical methods that work well in current computing environments. ..The book includes exercises and can be used as a test or supplementary text for various courses in modern statistics. It could serve as the |
| 出版日期 | Textbook 2003Latest edition |
| 關鍵詞 | Markov chain Monte Carlo; Monte Carlo Methods; Monte Carlo method; computational statistics; probability |
| 版次 | 2 |
| doi | https://doi.org/10.1007/b97336 |
| isbn_softcover | 978-1-4419-1808-6 |
| isbn_ebook | 978-0-387-21610-2Series ISSN 1431-8784 Series E-ISSN 2197-1706 |
| issn_series | 1431-8784 |
| copyright | Springer Science+Business Media New York 2003 |
|Archiver|手機版|小黑屋|
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