Takeaki Kariya, Bimal K. Sinha

Robustness of Statistical Tests (eBook, PDF)

Redaktion: Lieberman, Gerald L.; Olkin, Ingram

• Format: PDF

Produktbeschreibung

Robustness of Statistical Tests provides a general, systematic finite sample theory of the robustness of tests and covers the application of this theory to some important testing problems commonly considered under normality. This eight-chapter text focuses on the robustness that is concerned with the exact robustness in which the distributional or optimal property that a test carries under a normal distribution holds exactly under a nonnormal distribution.

Chapter 1 reviews the elliptically symmetric distributions and their properties, while Chapter 2 describes the representation theorem for the probability ration of a maximal invariant. Chapter 3 explores the basic concepts of three aspects of the robustness of tests, namely, null, nonnull, and optimality, as well as a theory providing methods to establish them. Chapter 4 discusses the applications of the general theory with the study of the robustness of the familiar Student's r-test and tests for serial correlation. This chapter also deals with robustness without invariance. Chapter 5 looks into the most useful and widely applied problems in multivariate testing, including the GMANOVA (General Multivariate Analysis of Variance). Chapters 6 and 7 tackle the robust tests for covariance structures, such as sphericity and independence and provide a detailed description of univariate and multivariate outlier problems. Chapter 8 presents some new robustness results, which deal with inference in two population problems.

This book will prove useful to advance graduate mathematical statistics students.

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 208
• Erscheinungstermin: 10. Mai 2014
• Englisch
• ISBN-13: 9781483266008
• Artikelnr.: 52993651