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Robust Statistics

简体网页||繁体网页
Ricardo A. Maronna 作者
Wiley
译者
2006-06-13 出版日期
436 页数
USD 110.00 价格
Hardcover
丛书系列
9780470010921 图书编码

Robust Statistics 在线电子书 图书标签: statistics  英语  統計學  數學  textbook統計  @網   


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Robust Statistics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Robust Statistics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Robust Statistics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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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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