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„A comprehensive introduction and discussion on the formal mathematical background behind qualitative and quantitative robustness is provided, and subsequent chapters delve into basic types of scale estimates, asymptotic minimax theory, regression, robust covariance, and robust design . . . it also serves as a valuable reference for researchers and practitioners who wish to study the statistical research associated with robust statistics“ (Mathematical Reviews, 2010)
A new edition of the classic, groundbreaking book on robuststatistics
Over twenty-five years after the publication of its predecessor, Robust Statistics, Second Edition continues to provide anauthoritative and systematic treatment of the topic. This newedition has been thoroughly updated and expanded to reflect thelatest advances in the field while also outlining the establishedtheory and applications for building a solid foundation in robuststatistics for both the theoretical and the appliedstatistician.
A comprehensive introduction and discussion on the formalmathematical background behind qualitative and quantitativerobustness is provided, and subsequent chapters delve into basictypes of scale estimates, asymptotic minimax theory, regression, robust covariance, and robust design. In addition to an extendedtreatment of robust regression, the Second Edition features fournew chapters covering:
* Robust Tests
* Small Sample Asymptotics
* Breakdown Point
* Bayesian Robustness
An expanded treatment of robust regression and pseudo-values isalso featured, and concepts, rather than mathematical completeness, are stressed in every discussion. Selected numerical algorithms forcomputing robust estimates and convergence proofs are providedthroughout the book, along with quantitative robustness informationfor a variety of estimates. A General Remarks section appears atthe beginning of each chapter and provides readers with amplemotivation for working with the presented methods andtechniques.
Robust Statistics, Second Edition is an ideal book forgraduate-level courses on the topic. It also serves as a valuablereference for researchers and practitioners who wish to study thestatistical research associated with robust statistics.
Over twenty-five years after the publication of its predecessor, Robust Statistics, Second Edition continues to provide anauthoritative and systematic treatment of the topic. This newedition has been thoroughly updated and expanded to reflect thelatest advances in the field while also outlining the establishedtheory and applications for building a solid foundation in robuststatistics for both the theoretical and the appliedstatistician.
A comprehensive introduction and discussion on the formalmathematical background behind qualitative and quantitativerobustness is provided, and subsequent chapters delve into basictypes of scale estimates, asymptotic minimax theory, regression, robust covariance, and robust design. In addition to an extendedtreatment of robust regression, the Second Edition features fournew chapters covering:
* Robust Tests
* Small Sample Asymptotics
* Breakdown Point
* Bayesian Robustness
An expanded treatment of robust regression and pseudo-values isalso featured, and concepts, rather than mathematical completeness, are stressed in every discussion. Selected numerical algorithms forcomputing robust estimates and convergence proofs are providedthroughout the book, along with quantitative robustness informationfor a variety of estimates. A General Remarks section appears atthe beginning of each chapter and provides readers with amplemotivation for working with the presented methods andtechniques.
Robust Statistics, Second Edition is an ideal book forgraduate-level courses on the topic. It also serves as a valuablereference for researchers and practitioners who wish to study thestatistical research associated with robust statistics.
