{"id":{"repo_id":"regina","oai_identifier":"oai:uregina.scholaris.ca:10294/14492"},"canonical_url":"https://search.dev.ndltd.org/etd/regina/oai:uregina.scholaris.ca:10294/14492","repository":{"repo_id":"regina","name":"University of Regina","base_url":"https://uregina.scholaris.ca/server/oai/request"},"display":{"title":"A Two-Parameter Lindley-Binomial Distribution: Properties and Applications","abstract":"The binomial distribution is a common and well known distribution that many situations and applications of binomial distribution can be found. In the real life anything that can be thought of a success or a failure can be considered as a Binomial distribution. However, this kind of instances does not fit to binomial distribution well at all the time. Therefore, in order to improve the ability of fitting various models, two-parameter Lindley distri- bution is used to combine with binomial distribution. In this thesis, a new generalized discrete distribution, that is named as two-parameter Lindley-binomial distribution, is introduced by compounding two-parameter Lindley distribution with binomial distribution. Several prob- abilistic properties of this proposed distribution such as the shape of proba- bility mass function, generating functions etc., are derived. Estimations for the parameters are obtained through method of moments, maximum like- lihood estimation and expectation-maximization algorithm. This proposed distribution is used to fit two real data sets and to test its goodness of fit. We also compared the performance of proposed distribution with that of bi- nomial and beta-binomial distributions. The results obtained from examples demonstrate some advantage of the distribution proposed in this thesis.","abstract_html":"The binomial distribution is a common and well known distribution that many situations and applications of binomial distribution can be found. In the real life anything that can be thought of a success or a failure can be considered as a Binomial distribution. However, this kind of instances does not fit to binomial distribution well at all the time. Therefore, in order to improve the ability of fitting various models, two-parameter Lindley distri- bution is used to combine with binomial distribution. In this thesis, a new generalized discrete distribution, that is named as two-parameter Lindley-binomial distribution, is introduced by compounding two-parameter Lindley distribution with binomial distribution. Several prob- abilistic properties of this proposed distribution such as the shape of proba- bility mass function, generating functions etc., are derived. Estimations for the parameters are obtained through method of moments, maximum like- lihood estimation and expectation-maximization algorithm. This proposed distribution is used to fit two real data sets and to test its goodness of fit. We also compared the performance of proposed distribution with that of bi- nomial and beta-binomial distributions. The results obtained from examples demonstrate some advantage of the distribution proposed in this thesis.","abstract_has_math":false,"creators":["Zhang, Xiaoqing"],"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":2021,"date_issued":"2021-06","date_published":"2021-06","updated_at":"2026-07-24T04:03:29Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/3907"],"render_values":[{"text":"https://doi.org/10.82465/3907","href":"https://doi.org/10.82465/3907","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10294/14492","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":["Zhang, Xiaoqing"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-12-13T17:40:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-12-13T17:40:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-06"]},{"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/10.82465/3907"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10294/14492"]}]},{"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. viii, 72 p."]},{"key":"dc:description.abstract","label":"Abstract","values":["The binomial distribution is a common and well known distribution that many situations and applications of binomial distribution can be found. In the real life anything that can be thought of a success or a failure can be considered as a Binomial distribution. However, this kind of instances does not fit to binomial distribution well at all the time. Therefore, in order to improve the ability of fitting various models, two-parameter Lindley distri- bution is used to combine with binomial distribution. In this thesis, a new generalized discrete distribution, that is named as two-parameter Lindley-binomial distribution, is introduced by compounding two-parameter Lindley distribution with binomial distribution. Several prob- abilistic properties of this proposed distribution such as the shape of proba- bility mass function, generating functions etc., are derived. Estimations for the parameters are obtained through method of moments, maximum like- lihood estimation and expectation-maximization algorithm. This proposed distribution is used to fit two real data sets and to test its goodness of fit. We also compared the performance of proposed distribution with that of bi- nomial and beta-binomial distributions. The results obtained from examples demonstrate some advantage of the distribution proposed in this thesis."]},{"key":"dc:title","label":"Title","values":["A Two-Parameter Lindley-Binomial Distribution: Properties and Applications"]}]}],"canonical_facts":{"dc:contributor.advisor":["Deng, DianLiang"],"dc:contributor.committeemember":["Volodin, Andrei"],"dc:creator":["Zhang, Xiaoqing"],"dc:date.accessioned":["2021-12-13T17:40:12Z"],"dc:date.available":["2021-12-13T17:40:12Z"],"dc:date.issued":["2021-06"],"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. viii, 72 p."],"dc:description.abstract":["The binomial distribution is a common and well known distribution that many situations and applications of binomial distribution can be found. In the real life anything that can be thought of a success or a failure can be considered as a Binomial distribution. However, this kind of instances does not fit to binomial distribution well at all the time. Therefore, in order to improve the ability of fitting various models, two-parameter Lindley distri- bution is used to combine with binomial distribution. In this thesis, a new generalized discrete distribution, that is named as two-parameter Lindley-binomial distribution, is introduced by compounding two-parameter Lindley distribution with binomial distribution. Several prob- abilistic properties of this proposed distribution such as the shape of proba- bility mass function, generating functions etc., are derived. Estimations for the parameters are obtained through method of moments, maximum like- lihood estimation and expectation-maximization algorithm. This proposed distribution is used to fit two real data sets and to test its goodness of fit. We also compared the performance of proposed distribution with that of bi- nomial and beta-binomial distributions. The results obtained from examples demonstrate some advantage of the distribution proposed in this thesis."],"dc:identifier.doi":["https://doi.org/10.82465/3907"],"dc:identifier.uri":["https://hdl.handle.net/10294/14492"],"dc:language.iso":["en"],"dc:publisher":["Faculty of Graduate Studies and Research, University of Regina"],"dc:title":["A Two-Parameter Lindley-Binomial Distribution: Properties and Applications"],"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":"2026-07-24T04:03:29Z"}