{"id":{"repo_id":"windsor","oai_identifier":"oai:uwindsor.scholaris.ca:20.500.14776/8214"},"canonical_url":"https://search.dev.ndltd.org/etd/windsor/oai:uwindsor.scholaris.ca:20.500.14776/8214","repository":{"repo_id":"windsor","name":"University of Windsor","base_url":"https://uwindsor.scholaris.ca/server/oai/request"},"display":{"title":"Monitoring Parameter Change in Autocorrelated Logistic Regression","abstract":"Monitoring changes in health care performances, financial markets, and industrial processes has recently gained momentum due to increased capability of computers and the availability of real-time data collection and storage software. As a consequence, there has been a growing demand in developing statistically rigorous methodologies for monitoring and change-point detection. In many practical situations, the data being monitored for the purpose of detecting changes, present serial correlations. Hussein (2011) is currently working on a new statistical procedure for monitoring changes in the coefficients of logistic regression model with AR( p)-type structure. The objective of this thesis is (a) to use Monte Carlo experiments to evaluate the average stopping times, probability of false alarm, and power of the proposed procedure; (b) to illustrate the usefulness of the method by using an IBM stock transactions data as well as data on rainfall.","abstract_html":"Monitoring changes in health care performances, financial markets, and industrial processes has recently gained momentum due to increased capability of computers and the availability of real-time data collection and storage software. As a consequence, there has been a growing demand in developing statistically rigorous methodologies for monitoring and change-point detection. In many practical situations, the data being monitored for the purpose of detecting changes, present serial correlations. Hussein (2011) is currently working on a new statistical procedure for monitoring changes in the coefficients of logistic regression model with AR( p)-type structure. The objective of this thesis is (a) to use Monte Carlo experiments to evaluate the average stopping times, probability of false alarm, and power of the proposed procedure; (b) to illustrate the usefulness of the method by using an IBM stock transactions data as well as data on rainfall.","abstract_has_math":false,"creators":["Khaleghei Ghosheh Balagh, Akram"],"institution":"University of Windsor","degree_name":"M.Sc.","degree_level":"Masters","degree_discipline":"Mathematics and Statistics","degree_department":null,"school":null,"contributors":["olsenc@uwindsor.ca"],"advisors":["Hussein, Abdulkadir Ali"],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01","date_published":"2011-01-01","updated_at":"2026-07-27T22:04:38Z","subjects":[],"languages":["en_CA"],"rights":[],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14776/8214","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["olsenc@uwindsor.ca"]},{"key":"dc:contributor.advisor","label":"Advisor","values":["Hussein, Abdulkadir Ali"]},{"key":"dc:creator","label":"Author","values":["Khaleghei Ghosheh Balagh, Akram"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-03 14:08"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-12-18 12:36","2025-07-03T18:08:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2011-01-01"]},{"key":"dc:type","label":"Dc Type","values":["info:eu-repo/semantics/masterThesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics and Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.Sc."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Windsor"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_CA"]},{"key":"dc:rights","label":"Dc Rights","values":["http://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14776/8214"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Monitoring changes in health care performances, financial markets, and industrial processes has recently gained momentum due to increased capability of computers and the availability of real-time data collection and storage software. 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