| 書目名稱 | Elements of Computational Statistics | | 編輯 | James E. Gentle | | 視頻video | http://file.papertrans.cn/308/307575/307575.mp4 | | 概述 | Includes supplementary material: | | 叢書名稱 | Statistics and Computing | | 圖書封面 |  | | 描述 | In recent years developments in statistics have to a great extent gone hand in hand with developments in computing. Indeed, many of the recent advances in statistics have been dependent on advances in computer science and techn- ogy. Many of the currently interesting statistical methods are computationally intensive, eitherbecausetheyrequireverylargenumbersofnumericalcompu- tions or because they depend on visualization of many projections of the data. The class of statistical methods characterized by computational intensity and the supporting theory for such methods constitute a discipline called “com- tational statistics”. (Here, I am following Wegman, 1988, and distinguishing “computationalstatistics”from“statisticalcomputing”, whichwetaketomean “computational methods, including numerical analysis, for statisticians”.) The computationally-intensive methods of modern statistics rely heavily on the developments in statistical computing and numerical analysis generally. Computational statistics shares two hallmarks with other “computational” sciences, such as computational physics, computational biology, and so on. One is a characteristic of the methodology: it is computationally in | | 出版日期 | Book 2002 | | 關(guān)鍵詞 | Approximation; Partition; Resampling; Ringe; Statistica; algebra; linear algebra; numerical analysis; optimi | | 版次 | 1 | | doi | https://doi.org/10.1007/b97337 | | isbn_softcover | 978-1-4419-3024-8 | | isbn_ebook | 978-0-387-21611-9Series ISSN 1431-8784 Series E-ISSN 2197-1706 | | issn_series | 1431-8784 | | copyright | Springer Science+Business Media New York 2002 |
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