Statistical methods for ranking data [Documento eletrónico] / Mayer Alvo, Philip L. H. Yu
Language: eng.Country: US - United States of America.Publication: New York, NY : Springer , 2014Description: XI, 273 p. : il.ISBN: 978-1-4939-1471-5.Series: Frontiers in Probability and the Statistical SciencesSubject - Topical Name: 3627Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT Online | Não Ficção | QA276.SPR FCT 81622 (Browse shelf(Opens below)) | 1 | Available |
Colocação: Online
This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.
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