Metric Methods for Analyzing Partially Ranked Data:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1985
|
| Schriftenreihe: | Lecture Notes in Statistics
34 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (X, 232p. 8 illus) |
| ISBN: | 9781461211068 9780387962887 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-1-4612-1106-8 |
Internformat
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Datensatz im Suchindex
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| author | Critchlow, Douglas E. |
| author_facet | Critchlow, Douglas E. |
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| author_sort | Critchlow, Douglas E. |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4612-1106-8 |
| format | Electronic eBook |
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| institution | BVB |
| isbn | 9781461211068 9780387962887 |
| issn | 0930-0325 |
| language | English |
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| spelling | Critchlow, Douglas E. Verfasser aut Metric Methods for Analyzing Partially Ranked Data by Douglas E. Critchlow New York, NY Springer New York 1985 1 Online-Ressource (X, 232p. 8 illus) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Statistics 34 0930-0325 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 Statistics Statistics, general Statistik Ranggeordnete Daten (DE-588)4121551-5 gnd rswk-swf Metrischer Raum (DE-588)4169745-5 gnd rswk-swf Rangstatistik (DE-588)4176945-4 gnd rswk-swf Ranggeordnete Daten (DE-588)4121551-5 s Metrischer Raum (DE-588)4169745-5 s 1\p DE-604 Rangstatistik (DE-588)4176945-4 s 2\p DE-604 https://doi.org/10.1007/978-1-4612-1106-8 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Critchlow, Douglas E. Metric Methods for Analyzing Partially Ranked Data Statistics Statistics, general Statistik Ranggeordnete Daten (DE-588)4121551-5 gnd Metrischer Raum (DE-588)4169745-5 gnd Rangstatistik (DE-588)4176945-4 gnd |
| subject_GND | (DE-588)4121551-5 (DE-588)4169745-5 (DE-588)4176945-4 |
| title | Metric Methods for Analyzing Partially Ranked Data |
| title_auth | Metric Methods for Analyzing Partially Ranked Data |
| title_exact_search | Metric Methods for Analyzing Partially Ranked Data |
| title_full | Metric Methods for Analyzing Partially Ranked Data by Douglas E. Critchlow |
| title_fullStr | Metric Methods for Analyzing Partially Ranked Data by Douglas E. Critchlow |
| title_full_unstemmed | Metric Methods for Analyzing Partially Ranked Data by Douglas E. Critchlow |
| title_short | Metric Methods for Analyzing Partially Ranked Data |
| title_sort | metric methods for analyzing partially ranked data |
| topic | Statistics Statistics, general Statistik Ranggeordnete Daten (DE-588)4121551-5 gnd Metrischer Raum (DE-588)4169745-5 gnd Rangstatistik (DE-588)4176945-4 gnd |
| topic_facet | Statistics Statistics, general Statistik Ranggeordnete Daten Metrischer Raum Rangstatistik |
| url | https://doi.org/10.1007/978-1-4612-1106-8 |
| work_keys_str_mv | AT critchlowdouglase metricmethodsforanalyzingpartiallyrankeddata |