9780470010921 - Robust Statistics: Theory and Methods (wiley Series in Probability and Statistics) by Maronna, Ricardo A.; Martin, Douglas R.; Yohai, Victor J. (28 results)

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Hardcover. Condition: New. 2nd Edition. John Wiley, Reprinted with corrections, Nov., 2006. XX+403 pages. New Hardcover. 9.25"x6.2"x1.1". be44.

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Condition: New. 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. Series: Wiley Series in Probability and Statistics. Num Pages: 436 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 231 x 158 x 37. Weight in Grams: 794. . 2006. 1st Edition. Hardcover. . . . .…

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Condition: New. 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. Series: Wiley Series in Probability and Statistics. Num Pages: 436 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 231 x 158 x 37. Weight in Grams: 794. . 2006. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Condition: New. Ricardo Maronna is a Professor in the Department of Mathematics, Faculty of Exact Sciences, National University of La Plata, Argentina, and researcher at C.I.C.P.B.A. He is the author of numerous research articles on robust statistics, especially in the are.

Hardcover. Condition: Brand New. 1st edition. 403 pages. 9.25x6.25x1.25 inches. In Stock.

Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

Hardcover. Condition: Brand New. 1st edition. 403 pages. 9.25x6.25x1.25 inches. In Stock. This item is printed on demand.

Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …