Robust Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Robust Statistics

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Ricardo A. Maronna 作者
Wiley
譯者
2006-06-13 出版日期
436 頁數
USD 110.00 價格
Hardcover
叢書系列
9780470010921 圖書編碼

Robust Statistics 在線電子書 圖書標籤: statistics  英語  統計學  數學  textbook統計  @網   


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Robust Statistics 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Robust Statistics 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Robust Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Robust Statistics - Maronna, Martin, Yohai

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Robust Statistics 在線電子書 著者簡介


Robust Statistics 在線電子書 著者簡介


Robust Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Robust Statistics 在線電子書 圖書描述

Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and different applications considered. Robust Statistics sets out to explain the use of robust methods and their theoretical justification. It provides an up-to-date overview of the theory and practical application of the robust statistical methods in regression, multivariate analysis, generalized linear models and time series. This unique book: * Enables the reader to select and use the most appropriate robust method for their particular statistical model. * Features computational algorithms for the core methods. * Covers regression methods for data mining applications. * Includes examples with real data and applications using the S-Plus robust statistics library. * Describes the theoretical and operational aspects of robust methods separately, so the reader can choose to focus on one or the other. * Supported by a supplementary website featuring time-limited S-Plus download, along with datasets and S-Plus code to allow the reader to reproduce the examples given in the book. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is ideal for researchers, practitioners and graduate students of statistics, electrical, chemical and biochemical engineering, and computer vision. There is also much to benefit researchers from other sciences, such as biotechnology, who need to use robust statistical methods in their work.

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