Robust Statistics

A new edition of the classic, groundbreaking book on robust
statistics

Over twenty-five years after the publication of its predecessor,
Robust Statistics, Second Edition continues to provide an
authoritative and systematic treatment of the topic. This new
edition has been thoroughly updated and expanded to reflect the
latest advances in the field while also outlining the established
theory and applications for building a solid foundation in robust
statistics for both the theoretical and the applied
statistician.

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. In addition to an extended
treatment of robust regression, the Second Edition features four
new chapters covering:

* Robust Tests

* Small Sample Asymptotics

* Breakdown Point

* Bayesian Robustness

An expanded treatment of robust regression and pseudo-values is
also featured, and concepts, rather than mathematical completeness,
are stressed in every discussion. Selected numerical algorithms for
computing robust estimates and convergence proofs are provided
throughout the book, along with quantitative robustness information
for a variety of estimates. A General Remarks section appears at
the beginning of each chapter and provides readers with ample
motivation for working with the presented methods and
techniques.

Robust Statistics, Second Edition is an ideal book for
graduate-level courses on the topic. It also serves as a valuable
reference for researchers and practitioners who wish to study the
statistical research associated with robust statistics.