书目名称 | Independent Random Sampling Methods |
编辑 | Luca Martino,David Luengo,Joaquín Míguez |
视频video | |
概述 | Presents an up-to-date survey of random sampling methods.Offers useful methods for practitioners together with detailed analyses for researchers in computational statistics.Covers random sampling from |
丛书名称 | Statistics and Computing |
图书封面 |  |
描述 | .This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code..The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques.. |
出版日期 | Book 2018 |
关键词 | Random sampling; Rejection samplers; Ratio-of-uniforms; Multidimensional random sampling; Markov chain M |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-319-72634-2 |
isbn_softcover | 978-3-030-10241-8 |
isbn_ebook | 978-3-319-72634-2Series ISSN 1431-8784 Series E-ISSN 2197-1706 |
issn_series | 1431-8784 |
copyright | Springer International Publishing AG, part of Springer Nature 2018 |