Frontiers in Probability and the Statistical Sciences

Statistical Methods for Ranking Data

Authors: Alvo, Mayer, Yu, Philip L.H.

  • 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
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eBook $79.99
price for USA (gross)
  • ISBN 978-1-4939-1471-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.00
price for USA
  • ISBN 978-1-4939-1470-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $109.00
price for USA
  • ISBN 978-1-4939-4781-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

Reviews

“The book is written at the level of a research monograph and is best suited for senior undergraduate and graduate students. The procedures are often illustrated by applications to real data sets. … the volume can very well serve as a textbook for courses on statistical methods for ranking data.” (Lucia Santamaria, zbMATH 1341.62001, 2016)

“This book is essentially a compilation of several research results contributed by the authors and their collaborators to the area of statistical analysis of ranking data. … This book is suitable for researchers and analysts in various domains like web commerce, health analytics, and so on, where invariably there is lot of data for analysis and inference. The two facets presented in the book, nonparametric statistics and modeling, offer valuable tools for analysis and inference.” (Laxminarayana Pillutla, Computing Reviews, May, 2015)


Table of contents (11 chapters)

  • Introduction

    Alvo, Mayer (et al.)

    Pages 1-5

  • Exploratory Analysis of Ranking Data

    Alvo, Mayer (et al.)

    Pages 7-21

  • Correlation Correlation Analysis of Paired Ranking Data

    Alvo, Mayer (et al.)

    Pages 23-53

  • Testing for Randomness, Agreement, and Interaction

    Alvo, Mayer (et al.)

    Pages 55-79

  • Block Designs

    Alvo, Mayer (et al.)

    Pages 81-104

Buy this book

eBook $79.99
price for USA (gross)
  • ISBN 978-1-4939-1471-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.00
price for USA
  • ISBN 978-1-4939-1470-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $109.00
price for USA
  • ISBN 978-1-4939-4781-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Statistical Methods for Ranking Data
Authors
Series Title
Frontiers in Probability and the Statistical Sciences
Copyright
2014
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4939-1471-5
DOI
10.1007/978-1-4939-1471-5
Hardcover ISBN
978-1-4939-1470-8
Softcover ISBN
978-1-4939-4781-2
Edition Number
1
Number of Pages
XI, 273
Number of Illustrations and Tables
18 b/w illustrations, 4 illustrations in colour
Topics