{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/22484"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/22484","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The use of nonnull models for ranks in nonparametric statistics","abstract":"\"A popular nonparametric measure of a monotone relation between two variables is Kendall's tau. Originally, most analysis of this statistic assumed the two variables were independent, while more recently there has been interest in finding \"\"nonnull\"\" models for the observations which allow types of dependence. One such model popularized by Mallows (1957, Annals of Mathematical Statistics) uses a one-parameter exponential family model with the canonical sufficient statistic being equivalent to Kendall's tau.\"","abstract_html":"&quot;A popular nonparametric measure of a monotone relation between two variables is Kendall&#x27;s tau. Originally, most analysis of this statistic assumed the two variables were independent, while more recently there has been interest in finding &quot;&quot;nonnull&quot;&quot; models for the observations which allow types of dependence. One such model popularized by Mallows (1957, Annals of Mathematical Statistics) uses a one-parameter exponential family model with the canonical sufficient statistic being equivalent to Kendall&#x27;s tau.&quot;","abstract_has_math":false,"creators":["Chung, Lyinn"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":["Marden, John I."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T13:41:20Z","date_published":"2011-05-07T13:41:20Z","updated_at":"2026-07-22T22:25:20Z","subjects":["Statistics"],"languages":["eng"],"rights":["Copyright 1989 Chung, Lyinn"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9010832","(UMI)AAI9010832"],"render_values":[{"text":"AAI9010832","href":null,"code":true},{"text":"(UMI)AAI9010832","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/22484","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Marden, John I."]},{"key":"dc:creator","label":"Author","values":["Chung, Lyinn"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T13:41:20Z","10000-01-01","1989"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Statistics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1989 Chung, Lyinn"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9010832","(UMI)AAI9010832","http://hdl.handle.net/2142/22484"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["\"A popular nonparametric measure of a monotone relation between two variables is Kendall's tau. Originally, most analysis of this statistic assumed the two variables were independent, while more recently there has been interest in finding \"\"nonnull\"\" models for the observations which allow types of dependence. One such model popularized by Mallows (1957, Annals of Mathematical Statistics) uses a one-parameter exponential family model with the canonical sufficient statistic being equivalent to Kendall's tau.\"","This thesis explores theoretical and practical aspects of this model. Asymptotic normality of the statistic is proved, and good asymptotic approximations for its mean and variance are found. It is shown that the Maximum Likelihood Estimator of the parameter is asymptotically normal. These results are obtained for the case with neither variable having any ties and for the case with one variable being an indicator variable, in which case the statistic becomes the Mann-Whitney statistic for comparing two groups. Some extensions are made to comparing several groups.","In order to understand how well the model works in practice, its performance is evaluated under various bivariate and location-family models. It appears to be a good proxy for many models.","Made available in DSpace on 2011-05-07T13:41:20Z (GMT). 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Originally, most analysis of this statistic assumed the two variables were independent, while more recently there has been interest in finding \"\"nonnull\"\" models for the observations which allow types of dependence. One such model popularized by Mallows (1957, Annals of Mathematical Statistics) uses a one-parameter exponential family model with the canonical sufficient statistic being equivalent to Kendall's tau.\"","This thesis explores theoretical and practical aspects of this model. Asymptotic normality of the statistic is proved, and good asymptotic approximations for its mean and variance are found. It is shown that the Maximum Likelihood Estimator of the parameter is asymptotically normal. These results are obtained for the case with neither variable having any ties and for the case with one variable being an indicator variable, in which case the statistic becomes the Mann-Whitney statistic for comparing two groups. 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No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9010832.pdf: 2602370 bytes, checksum: a9ae0f76de2fc33c1f4c59656c982247 (MD5) Previous issue date: 1989","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:57:56Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:27:12-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"],"dc:identifier":["AAI9010832","(UMI)AAI9010832","http://hdl.handle.net/2142/22484"],"dc:language":["eng"],"dc:rights":["Copyright 1989 Chung, Lyinn"],"dc:subject":["Statistics"],"dc:title":["The use of nonnull models for ranks in nonparametric statistics"],"dc:type":["text"],"thesis:degree_discipline":["Statistics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:20Z"}