{"id":{"repo_id":"regina","oai_identifier":"oai:uregina.scholaris.ca:10294/9253"},"canonical_url":"https://search.dev.ndltd.org/etd/regina/oai:uregina.scholaris.ca:10294/9253","repository":{"repo_id":"regina","name":"University of Regina","base_url":"https://uregina.scholaris.ca/server/oai/request"},"display":{"title":"New Multivariate Zero-Inflated Beta-Binomial Distribution","abstract":"The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and zero-inflated model has a better performance on analyzing the data with excess zeros. For dealing with the data with over-dispersion and extra zeros together, zero-inflated beta-binomial model is created. Likelihood- based inferences procedures include the induction of estimating parameters of the MZIBB model via Newton-Raphson algorithm, Fisher scoring algorithm, and EM algorithm. The score test and likelihood ratio test are derived for testing the significance of zero-inflation parameter ω. The performance of the EM algorithm is evaluated by giving different group settings of parameters in the simulation study. In the end, real data which is about the effect of pesticide using for killing whiteflies are studied and analyzed by using MZIBB model.","abstract_html":"The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and zero-inflated model has a better performance on analyzing the data with excess zeros. For dealing with the data with over-dispersion and extra zeros together, zero-inflated beta-binomial model is created. Likelihood- based inferences procedures include the induction of estimating parameters of the MZIBB model via Newton-Raphson algorithm, Fisher scoring algorithm, and EM algorithm. The score test and likelihood ratio test are derived for testing the significance of zero-inflation parameter ω. The performance of the EM algorithm is evaluated by giving different group settings of parameters in the simulation study. In the end, real data which is about the effect of pesticide using for killing whiteflies are studied and analyzed by using MZIBB model.","abstract_has_math":false,"creators":["Ji, Bowen"],"institution":"Faculty of Graduate Studies and Research, University of Regina","degree_name":"Master of Science (MSc)","degree_level":"Master's","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":[],"advisors":["Deng, Dianliang"],"committee_chairs":[],"committee_members":["Volodin, Andrei"],"year":2019,"date_issued":"2019-12","date_published":"2019-12","updated_at":"2026-07-24T04:03:45Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/4833"],"render_values":[{"text":"https://doi.org/10.82465/4833","href":"https://doi.org/10.82465/4833","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10294/9253","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Deng, Dianliang"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Volodin, Andrei"]},{"key":"dc:creator","label":"Author","values":["Ji, Bowen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-08-29T19:03:06Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-08-29T19:03:06Z"]},{"key":"dc:date.issued","label":"Date","values":["2019-12"]},{"key":"dc:publisher","label":"Institution","values":["Faculty of Graduate Studies and Research, University of Regina"]},{"key":"dc:type","label":"Dc Type","values":["master thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master's"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MSc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Faculty of Graduate Studies and Research, University of Regina"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/4833"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10294/9253"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Statistics, University of Regina. vi, 62 p."]},{"key":"dc:description.abstract","label":"Abstract","values":["The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and zero-inflated model has a better performance on analyzing the data with excess zeros. For dealing with the data with over-dispersion and extra zeros together, zero-inflated beta-binomial model is created. Likelihood- based inferences procedures include the induction of estimating parameters of the MZIBB model via Newton-Raphson algorithm, Fisher scoring algorithm, and EM algorithm. The score test and likelihood ratio test are derived for testing the significance of zero-inflation parameter ω. The performance of the EM algorithm is evaluated by giving different group settings of parameters in the simulation study. In the end, real data which is about the effect of pesticide using for killing whiteflies are studied and analyzed by using MZIBB model."]},{"key":"dc:title","label":"Title","values":["New Multivariate Zero-Inflated Beta-Binomial Distribution"]}]}],"canonical_facts":{"dc:contributor.advisor":["Deng, Dianliang"],"dc:contributor.committeemember":["Volodin, Andrei"],"dc:creator":["Ji, Bowen"],"dc:date.accessioned":["2020-08-29T19:03:06Z"],"dc:date.available":["2020-08-29T19:03:06Z"],"dc:date.issued":["2019-12"],"dc:description":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Statistics, University of Regina. vi, 62 p."],"dc:description.abstract":["The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and zero-inflated model has a better performance on analyzing the data with excess zeros. For dealing with the data with over-dispersion and extra zeros together, zero-inflated beta-binomial model is created. Likelihood- based inferences procedures include the induction of estimating parameters of the MZIBB model via Newton-Raphson algorithm, Fisher scoring algorithm, and EM algorithm. The score test and likelihood ratio test are derived for testing the significance of zero-inflation parameter ω. The performance of the EM algorithm is evaluated by giving different group settings of parameters in the simulation study. In the end, real data which is about the effect of pesticide using for killing whiteflies are studied and analyzed by using MZIBB model."],"dc:identifier.doi":["https://doi.org/10.82465/4833"],"dc:identifier.uri":["https://hdl.handle.net/10294/9253"],"dc:language.iso":["en"],"dc:publisher":["Faculty of Graduate Studies and Research, University of Regina"],"dc:title":["New Multivariate Zero-Inflated Beta-Binomial Distribution"],"dc:type":["master thesis"],"thesis:degree_discipline":["Statistics"],"thesis:degree_level":["Master's"],"thesis:degree_name":["Master of Science (MSc)"],"thesis:institution_name":["Faculty of Graduate Studies and Research, University of Regina"]},"updated_at":"2026-07-24T04:03:45Z"}