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Statistics - Statistical Theory and Methods | Statistical Methods for Ranking Data

Statistical Methods for Ranking Data

Alvo, Mayer, Yu, Philip L.H.

2014, XI, 273 p. 22 illus., 4 illus. in color.

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  • Contains a unified treatment of both inference and modeling for ranking data
  • Contains comprehensive software to enable the practitioner to access the methods
  • Contains illustrative data sets and exercises so that it can be used as a textbook in a graduate course

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.

Content Level » Research

Keywords » Block designs - Exploratory data analysis - Missing and tied data - Probabilistic and statistical modeling - Ranking data

Related subjects » Computational Statistics - Database Management & Information Retrieval - Statistical Theory and Methods - Statistics

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