The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement error models concentrates mainly on the rank procedures, less sensitive to errors than other procedures. This book will be an invaluable resource for researchers and postgraduate students in statistics and mathematics.
Features
• Provides a systematic, practical treatment of robust statistical methods
• Offers a rigorous treatment of the whole range of robust methods, including the sequential versions of estimators, their moment convergence, and compares their asymptotic and finite-sample behavior
• The extended account of multivariate models includes the admissibility, shrinkage effects and unbiasedness of two-sample tests
• Illustrates the small sensitivity of the rank procedures in the measurement error model
• Emphasizes the computational aspects, supplies many examples and illustrations, and provides the own procedures of the authors in the R software on the book’s website
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Jana Jurečková is a Professor of Statistics at the Charles University, Prague.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement error models concentrates mainly on the rank procedures, less sensitive to errors than other procedures. This book will be an invaluable resource for researchers and postgraduate students in statistics and mathematics.Features Provides a systematic, practical treatment of robust statistical methods Offers a rigorous treatment of the whole range of robust methods, including the sequential versions of estimators, their moment convergence, and compares their asymptotic and finite-sample behavior The extended account of multivariate models includes the admissibility, shrinkage effects and unbiasedness of two-sample tests Illustrates the small sensitivity of the rank procedures in the measurement error model Emphasizes the computational aspects, supplies many examples and illustrations, and provides the own procedures of the authors in the R software on the books website The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781138035362
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