A Logspline method of estimating an unknown density function f based on sample data is studied. Our approach is to use maximum likelihood estimation to estimate the unknown density function from a space of linear splines that have a finite number of fixed uniform knots. In the end of this thesis, the method is applied to a real survival data set of lung cancer patients.
","abstract_html":"<p>A Logspline method of estimating an unknown density function <em>f</em> based on sample data is studied. Our approach is to use maximum likelihood estimation to estimate the unknown density function from a space of linear splines that have a finite number of fixed uniform knots. In the end of this thesis, the method is applied to a real survival data set of lung cancer patients.</p>","abstract_has_math":false,"creators":["Chen, Yong"],"institution":null,"degree_name":"MS (Master of Science)","degree_level":"Thesis - restricted","degree_discipline":"Mathematical Sciences","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-08-18T07:00:00Z","date_published":"2004-08-18T07:00:00Z","updated_at":"2026-07-24T02:19:35Z","subjects":["Density estimation","Maximum likelihood","Splines","Survival analysis","Physical Sciences and Mathematics"],"languages":[],"rights":["Copyright by the authors."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.etsu.edu/etd/907","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Chen, Yong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2004-08-18T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - restricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS (Master of Science)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Density estimation","Maximum likelihood","Splines","Survival analysis","Physical Sciences and Mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright by the authors."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.etsu.edu/context/etd/article/2064/viewcontent/ChenY070604f.pdf","https://dc.etsu.edu/etd/907"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A Logspline method of estimating an unknown density function f based on sample data is studied. Our approach is to use maximum likelihood estimation to estimate the unknown density function from a space of linear splines that have a finite number of fixed uniform knots. In the end of this thesis, the method is applied to a real survival data set of lung cancer patients.
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