Introducing concepts, theory, and applications, Robust Statistics is accessible to a broad audience, avoiding allusions to high-powered mathematics while emphasizing ideas, heuristics, and background. The text covers the approach based on the influence function (the effect of an outlier on an estimater, for example) and related notions such as the breakdown point. It also treats the change-of-variance function, fundamental concepts and results in the framework of estimation of a single parameter, and applications to estimation of covariance matrices and regression parameters. Robust Statistics is a leading-edge resource suitable for use both as a textbook or a reference on robust statistics for all practitioners and students.

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A highly detailed, yet readable treatment of the growing field of robust statistics--the statistics of approximate parametric models. Introducing concepts, theory, and applications, this work is designed to be accessible to a broad audience, avoiding allusions to high-powered mathematics while emphasizing ideas, heuristics, and background. It covers the approach based on the influence function (the effect of an outlier on an estimater, for example) and related notions such as the breakdown point. Also treats the change-of-variance function, fundamental concepts and results in the framework of estimation of a single parameter, and applications to estimation of covariance matrices and regression parameters.

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