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This book provides a systematic account of robust statistical methods, an area where the existing literature is dated, narrow, or treated in an overly theoretical manner. The authors discuss the entire range of robust statistical methods at an accessible level appropriate for students at a Master's level or beyond. The treatment covers differentiable statistical functions, influence functions, asymptotic distributions, and much more. It also provides numerous examples and exercises, as well as computational algorithms using the R software package for applications of robust statistical methods. Outstanding for course work, this text is also a valuable reference for statisticians and quantitative scientists.