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Research in robust statistics is flourishing, and since the first edition of this book was published many important advances have been made in this area. However, there are relatively few books covering robust statistics, and even fewer that cover the subject in a comprehensive and definitive manner. This new edition will fulfill the need for a good upΓÇôtoΓÇôdate text that presents a broad overview of the theory of robust statistics, integrated with applications and computing. Updated to focus on the use of the popular software package R , it will feature inΓÇôdepth coverage of the key methodology, including regression, multivariate analysis, and time series. The book will be illustrated throughout by a range of examples and applications, and supported by a companion website featuring data sets and R code to allow the reader to reproduce the examples given in the book.
Robust Statistics fills the need for a solid, up-to-date text that presents a broad overview of the theory of robust statistics, integrated with applications and computing. The book features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series.
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