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Robust statistics : theory and methods / Ricardo A. Maronna, R. Douglas Martin, Víctor J. Yohai.

By: Contributor(s): Material type: TextTextSeries: Wiley series in probability and statisticsPublisher: Chichester, England : J. Wiley, [2006]Copyright date: ©2006Description: xx, 403 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0470010924
  • 9780470010921
Subject(s): DDC classification:
  • 519.5 22
LOC classification:
  • QA276 .M37 2006
Contents:
Location and scale -- Measuring robustness -- Linear regression 1 -- Linear regression 2 -- Multivariate analysis -- Generalized linear models -- Time series -- Numerical algorithms -- Asymptotic theory of M-estimates -- Robust methods in S-plus -- Description of data sets.
Review: "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 robust statistical methods in regression, multivariate analysis, generalized linear models and time series." "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."--Jacket.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book North Campus North Campus Main Collection 519.5 MAR (Browse shelf(Opens below)) 1 Available A557304B

Includes bibliographical references and index.

Location and scale -- Measuring robustness -- Linear regression 1 -- Linear regression 2 -- Multivariate analysis -- Generalized linear models -- Time series -- Numerical algorithms -- Asymptotic theory of M-estimates -- Robust methods in S-plus -- Description of data sets.

"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 robust statistical methods in regression, multivariate analysis, generalized linear models and time series." "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."--Jacket.

Machine converted from AACR2 source record.

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