Metric Methods for Analyzing Partially Ranked Data

Name: Metric Methods for Analyzing Partially Ranked Data
Brand: Springer-Verlag New York Inc.
SKU: 9780387962887
Price: 65687 HUF
Availability: InStock

Szerző: Douglas E. Critchlow

Nyelv:

Kötés: Puha kötésű

Kiadó: Springer-Verlag New York Inc.

Elérhetőség: Beszállítói készleten

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A full ranking of n items is simply an ordering of all these items, of the form: first choice, secon...

Információk a könyvről

Szerző

Douglas E. Critchlow

Nyelv

Angol

Kötés

Könyv - Puha kötésű

oldal

216

EAN

9780387962887

ISBN

0387962883

Enbook ID

01384651

Kiadó

Springer-Verlag New York Inc.

Súly

730

Méretek

155 x 235 x 13

Teljes leírás

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.

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Metric Methods for Analyzing Partially Ranked Data

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