{"id":{"repo_id":"gsu","oai_identifier":"oai:digitalcommons.georgiasouthern.edu:etd-1848"},"canonical_url":"https://search.dev.ndltd.org/etd/gsu/oai:digitalcommons.georgiasouthern.edu:etd-1848","repository":{"repo_id":"gsu","name":"Georgia Southern University","base_url":"https://digitalcommons.georgiasouthern.edu/do/oai/"},"display":{"title":"The Dagum-Weibull and Related Weighted Distributions","abstract":"<p>In this thesis, a new class of distributions called the Dagum-Weibull family of distributions is constructed via the \\Transform-Transformer\" principle. This class of distributions turns out to be a weighted distribution with weights obtained via hazard functions. The class of Dagum-Weibull distributions contains several submodels such as length-biased Dagum-Weibull (LBDW), proportional hazard moment DagumWeibull (PHMDW), Dagum-Weibull (DW), and Dagum distributions as special cases. Some fundamental results on the weighted, parent Dagum-Weibull and related distributions are presented. Probability weighted moments and the resulting weighted distributions are constructed and studied. Inequality measures, entropy, and Fisher information are derived. Estimates of model parameters are obtained and some applications as well as numerical examples are given.</p>","abstract_html":"&lt;p&gt;In this thesis, a new class of distributions called the Dagum-Weibull family of distributions is constructed via the \\Transform-Transformer&quot; principle. This class of distributions turns out to be a weighted distribution with weights obtained via hazard functions. The class of Dagum-Weibull distributions contains several submodels such as length-biased Dagum-Weibull (LBDW), proportional hazard moment DagumWeibull (PHMDW), Dagum-Weibull (DW), and Dagum distributions as special cases. Some fundamental results on the weighted, parent Dagum-Weibull and related distributions are presented. Probability weighted moments and the resulting weighted distributions are constructed and studied. Inequality measures, entropy, and Fisher information are derived. Estimates of model parameters are obtained and some applications as well as numerical examples are given.&lt;/p&gt;","abstract_has_math":false,"creators":["Kimitei, Benson"],"institution":null,"degree_name":"Master of Science in Mathematics (M.S.)","degree_level":"Thesis (restricted to Georgia Southern)","degree_discipline":"Department of Mathematical Sciences","degree_department":null,"school":null,"contributors":["Charles Champ","Hani Samawi"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T02:27:41Z","subjects":["ETD","Weighted Distribution","Dagum-Weibull Distribution","Related Distributions","Applied Statistics","Probability","Statistics and Probability"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.georgiasouthern.edu/etd/845","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Charles Champ","Hani Samawi"]},{"key":"dc:creator","label":"Author","values":["Kimitei, Benson"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2013-09-17T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Department of Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis (restricted to Georgia Southern)"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Mathematics (M.S.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["ETD","Weighted Distribution","Dagum-Weibull Distribution","Related Distributions","Applied Statistics","Probability","Statistics and Probability"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.georgiasouthern.edu/etd/845"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>In this thesis, a new class of distributions called the Dagum-Weibull family of distributions is constructed via the \\Transform-Transformer\" principle. This class of distributions turns out to be a weighted distribution with weights obtained via hazard functions. The class of Dagum-Weibull distributions contains several submodels such as length-biased Dagum-Weibull (LBDW), proportional hazard moment DagumWeibull (PHMDW), Dagum-Weibull (DW), and Dagum distributions as special cases. Some fundamental results on the weighted, parent Dagum-Weibull and related distributions are presented. Probability weighted moments and the resulting weighted distributions are constructed and studied. Inequality measures, entropy, and Fisher information are derived. Estimates of model parameters are obtained and some applications as well as numerical examples are given.</p>"]},{"key":"dc:title","label":"Title","values":["The Dagum-Weibull and Related Weighted Distributions"]}]}],"canonical_facts":{"dc:contributor":["Charles Champ","Hani Samawi"],"dc:creator":["Kimitei, Benson"],"dc:date.available":["2013-09-17T07:00:00Z"],"dc:description.abstract":["<p>In this thesis, a new class of distributions called the Dagum-Weibull family of distributions is constructed via the \\Transform-Transformer\" principle. This class of distributions turns out to be a weighted distribution with weights obtained via hazard functions. The class of Dagum-Weibull distributions contains several submodels such as length-biased Dagum-Weibull (LBDW), proportional hazard moment DagumWeibull (PHMDW), Dagum-Weibull (DW), and Dagum distributions as special cases. Some fundamental results on the weighted, parent Dagum-Weibull and related distributions are presented. Probability weighted moments and the resulting weighted distributions are constructed and studied. Inequality measures, entropy, and Fisher information are derived. Estimates of model parameters are obtained and some applications as well as numerical examples are given.</p>"],"dc:identifier":["https://digitalcommons.georgiasouthern.edu/etd/845"],"dc:subject":["ETD","Weighted Distribution","Dagum-Weibull Distribution","Related Distributions","Applied Statistics","Probability","Statistics and Probability"],"dc:title":["The Dagum-Weibull and Related Weighted Distributions"],"thesis:degree_discipline":["Department of Mathematical Sciences"],"thesis:degree_level":["Thesis (restricted to Georgia Southern)"],"thesis:degree_name":["Master of Science in Mathematics (M.S.)"]},"updated_at":"2026-07-24T02:27:41Z"}