{"id":{"repo_id":"regina","oai_identifier":"oai:uregina.scholaris.ca:10294/15022"},"canonical_url":"https://search.dev.ndltd.org/etd/regina/oai:uregina.scholaris.ca:10294/15022","repository":{"repo_id":"regina","name":"University of Regina","base_url":"https://uregina.scholaris.ca/server/oai/request"},"display":{"title":"The Zero-Truncated Poisson-Weighted Exponential Distribution with Applications","abstract":"This research proposes a new distribution for non-zero count data, namely the zero-truncated Poisson-weighted exponential distribution (ZTPWE). The Poisson- weighted exponential distribution(P-WE) has been proved to be a flexible two-parameter distribution; therefore, Zero-truncated models can be used to investigate data with- out zero counts. The combination of two such methods will be discussed in two parts. In the first part (the theoretical part), the probability mass function is derived from two methods. Then theoretical properties of the zero-truncated Poisson weighted exponential distribution are discussed: such as probability generating function, moment generating function, characteristic function, and moments. Furthermore, the method of maximum likelihood estimation is applied to estimate the parameters. In the second part, software simulations and fittings of two real data sets are discussed. The performance of the new model will be compared with other proposed zero-truncated models. i","abstract_html":"This research proposes a new distribution for non-zero count data, namely the zero-truncated Poisson-weighted exponential distribution (ZTPWE). The Poisson- weighted exponential distribution(P-WE) has been proved to be a flexible two-parameter distribution; therefore, Zero-truncated models can be used to investigate data with- out zero counts. The combination of two such methods will be discussed in two parts. In the first part (the theoretical part), the probability mass function is derived from two methods. Then theoretical properties of the zero-truncated Poisson weighted exponential distribution are discussed: such as probability generating function, moment generating function, characteristic function, and moments. Furthermore, the method of maximum likelihood estimation is applied to estimate the parameters. In the second part, software simulations and fittings of two real data sets are discussed. The performance of the new model will be compared with other proposed zero-truncated models. i","abstract_has_math":false,"creators":["Qin, Jin"],"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":["Volodin, Andrei"],"committee_chairs":[],"committee_members":["Deng, DianLiang"],"year":2021,"date_issued":"2021-10","date_published":"2021-10","updated_at":"2026-07-24T04:03:47Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/4922"],"render_values":[{"text":"https://doi.org/10.82465/4922","href":"https://doi.org/10.82465/4922","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10294/15022","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Volodin, Andrei"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Deng, DianLiang"]},{"key":"dc:creator","label":"Author","values":["Qin, Jin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-08-05T17:37:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-08-05T17:37:15Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-10"]},{"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/10.82465/4922"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10294/15022"]}]},{"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. vii, 63 p"]},{"key":"dc:description.abstract","label":"Abstract","values":["This research proposes a new distribution for non-zero count data, namely the zero-truncated Poisson-weighted exponential distribution (ZTPWE). The Poisson- weighted exponential distribution(P-WE) has been proved to be a flexible two-parameter distribution; therefore, Zero-truncated models can be used to investigate data with- out zero counts. The combination of two such methods will be discussed in two parts. In the first part (the theoretical part), the probability mass function is derived from two methods. Then theoretical properties of the zero-truncated Poisson weighted exponential distribution are discussed: such as probability generating function, moment generating function, characteristic function, and moments. Furthermore, the method of maximum likelihood estimation is applied to estimate the parameters. In the second part, software simulations and fittings of two real data sets are discussed. The performance of the new model will be compared with other proposed zero-truncated models. i"]},{"key":"dc:title","label":"Title","values":["The Zero-Truncated Poisson-Weighted Exponential Distribution with Applications"]}]}],"canonical_facts":{"dc:contributor.advisor":["Volodin, Andrei"],"dc:contributor.committeemember":["Deng, DianLiang"],"dc:creator":["Qin, Jin"],"dc:date.accessioned":["2022-08-05T17:37:15Z"],"dc:date.available":["2022-08-05T17:37:15Z"],"dc:date.issued":["2021-10"],"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. vii, 63 p"],"dc:description.abstract":["This research proposes a new distribution for non-zero count data, namely the zero-truncated Poisson-weighted exponential distribution (ZTPWE). The Poisson- weighted exponential distribution(P-WE) has been proved to be a flexible two-parameter distribution; therefore, Zero-truncated models can be used to investigate data with- out zero counts. The combination of two such methods will be discussed in two parts. In the first part (the theoretical part), the probability mass function is derived from two methods. Then theoretical properties of the zero-truncated Poisson weighted exponential distribution are discussed: such as probability generating function, moment generating function, characteristic function, and moments. Furthermore, the method of maximum likelihood estimation is applied to estimate the parameters. In the second part, software simulations and fittings of two real data sets are discussed. The performance of the new model will be compared with other proposed zero-truncated models. i"],"dc:identifier.doi":["https://doi.org/10.82465/4922"],"dc:identifier.uri":["https://hdl.handle.net/10294/15022"],"dc:language.iso":["en"],"dc:publisher":["Faculty of Graduate Studies and Research, University of Regina"],"dc:title":["The Zero-Truncated Poisson-Weighted Exponential Distribution with 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":"2026-07-24T04:03:47Z"}