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Metric Methods For Analyzing Partially Ranked Data (lecture Notes In Statistics) by Douglas E. Critchlow (auth.) is a nonfiction available to read on EtoBox.

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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

Who reads Metric Methods For Analyzing Partially Ranked Data (lecture Notes In Statistics)?

Author

Douglas E. Critchlow (auth.)

Publisher

Springer-Verlag New York

Published

1985

Language

EN

ISBN

9781461211068

Category

nonfiction

Subjects

Mathematics, Stem