Rankings and Preferences

New Results in Weighted Correlation and Weighted Principal Component Analysis with Applications

  • Joaquim Pinto da Costa

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Table of contents

  1. Front Matter
    Pages i-x
  2. Joaquim Pinto da Costa
    Pages 1-7
  3. Joaquim Pinto da Costa
    Pages 9-27
  4. Joaquim Pinto da Costa
    Pages 29-38
  5. Joaquim Pinto da Costa
    Pages 69-73
  6. Back Matter
    Pages 75-91

About this book


This book examines in detail the correlation, more precisely the weighted correlation, and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis.

We also introduce new methods of dimension reduction and clustering for time series data, and describe some theoretical results on the weighted correlation coefficients in separate sections.


microarray data principal component analysis ranking time series weighted correlation

Authors and affiliations

  • Joaquim Pinto da Costa
    • 1
  1. 1.Department of MathematicsUniversity of PortoPortoPortugal

Bibliographic information

  • DOI
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-662-48343-5
  • Online ISBN 978-3-662-48344-2
  • Series Print ISSN 2191-544X
  • Series Online ISSN 2191-5458
  • Buy this book on publisher's site
Industry Sectors
Materials & Steel
Health & Hospitals
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Energy, Utilities & Environment
Oil, Gas & Geosciences