An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.
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Robert G. Staudte and Simon J. Sheather are the authors of Robust Estimation and Testing, published by Wiley.
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Hardcover. First Edition, First Printing. Octavo, xii, xix, 351 pages. In Very Good condition with a Very Good minus dust jacket. Spine blue with light blue lettering. Slight shelf wear with mild age toning to the rear and minor edge wear with previous bookshop's sticker to the rear. Boards have slight cocking to the spine and two faint streaks to the rear. Text block has extremely light wear to edges and advertisements printed to end papers. CD in pouch adhered to rear pastedown. First Edition, First Printing. 1371245. FP New Rockville Stock. Artikel-Nr. 1371245
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Zustand: New. An introduction to the theory and methods of robust statistics, which aims to illustrate the need for robust procedures in a variety of statistical contexts, and to develop the techniques and concepts useful in the analysis of new statistical models and pro. Artikel-Nr. 446918301
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Buch. Zustand: Neu. Neuware - An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems. Artikel-Nr. 9780471855477
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