Metric Methods for Analyzing Partially Ranked Data

  • Douglas E. Critchlow
Part of the Lecture Notes in Statistics book series (LNS, volume 34)

Table of contents

  1. Front Matter
    Pages I-X
  2. Douglas E. Critchlow
    Pages 1-4
  3. Douglas E. Critchlow
    Pages 5-11
  4. Douglas E. Critchlow
    Pages 33-79
  5. Douglas E. Critchlow
    Pages 80-96
  6. Douglas E. Critchlow
    Pages 97-129
  7. Back Matter
    Pages 130-216

About this book

Introduction

A full ranking of n items is simply an ordering of all these items, of the form: first choice, second choice, •. . , n-th choice. If two judges each rank the same n items, statisticians have used various metrics to measure the closeness of the two rankings, including Ken­ dall's tau, Spearman's rho, Spearman's footrule, Ulam's metric, Hal1l11ing distance, and Cayley distance. These metrics have been em­ ployed in many contexts, in many applied statistical and scientific problems. Thi s monograph presents genera 1 methods for extendi ng these metri cs to partially ranked data. Here "partially ranked data" refers, for instance, to the situation in which there are n distinct items, but each judge specifies only his first through k-th choices, where k < n. More complex types of partially ranked data are also investigated. Group theory is an important tool for extending the metrics. Full rankings are identified with elements of the permutation group, whereas partial rankings are identified with points in a coset space of the permutation group. The problem thus becomes one of ex­ tending metrics on the permutation group to metrics on a coset space of the permutation group. To carry out the extens"ions, two novel methods -- the so-called Hausdorff and fixed vector methods -- are introduced and implemented, which exploit this group-theoretic structure. Various data-analytic applications of metrics on fully ranked data have been presented in the statistical literature.

Keywords

Fitting Likelihood Variance data analysis multidimensional scaling

Authors and affiliations

  • Douglas E. Critchlow
    • 1
  1. 1.Department of StatisticsPurdue UniversityWest LafayetteUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1106-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 1985
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-96288-7
  • Online ISBN 978-1-4612-1106-8
  • Series Print ISSN 0930-0325
  • About this book