Alvo, Mayer Yu, Philip L. H. Parametric approach to nonparametric statistics 9783319941523

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Автор: Alvo, Mayer Yu, Philip L. H.
Название: Parametric approach to nonparametric statistics
ISBN: 9783319941523
Издательство: Springer
Классификация:

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ISBN-10: 3319941526
Обложка/Формат: Hardcover
Страницы: 279
Вес: 1.04 кг.
Дата издания: 23.10.2018
Серия: Springer series in the data sciences
Язык: English
Издание: 1st ed. 2018
Иллюстрации: 1 illustrations, color; 14 illustrations, black and white; viii, 272 p. 15 illus.
Размер: 316 x 358 x 20
Читательская аудитория: General (us: trade)
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter.This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.
Дополнительное описание: I. Introduction and Fundamentals.- Introduction.- Fundamental Concepts in Parametric Inference.- II. Modern Nonparametric Statistical Methods.- Smooth Goodness of Fit Tests.- One-Sample and Two-Sample Problems.- Multi-Sample Problems.- Tests for Trend and

Parametric approach to nonparametric statistics, Alvo, Mayer Yu, Philip L. H.