{"id":{"repo_id":"ttu","oai_identifier":"oai:ttu-ir.tdl.org:2346/72355"},"canonical_url":"https://search.dev.ndltd.org/etd/ttu/oai:ttu-ir.tdl.org:2346/72355","repository":{"repo_id":"ttu","name":"Texas Technology University","base_url":"https://ttu-ir.tdl.org/server/oai/request"},"display":{"title":"Inference for the survival function of the linearly decreasing stress Weibull","abstract":"The survival function is defined as the probability that a person or an object will survive beyond a specified time point. It is used in many applications including human mortality. It is also known as the survivor function or reliability function. The Weibull distribution has long drawn the attention of statisticians for modeling the reliability of systems. In this thesis, making inferences for the survival function of a Weibull system which is exposed to linearly decreasing stress is of concern. The derivation of the Linearly Decreasing Stress Weibull first appears in Guenther (2014). Parameters will be estimated using maximum likelihood estimation. The approximate normality of the maximum likelihood estimate of the survival function will be studied through a small scale simulation study. Various methods for finding confidence intervals of the survival function of a Linearly Decreasing Stress Weibull system are given. A large-scale simulation study will also be conducted to study the effectiveness of the resulting confidence intervals. The simulation study will also allow for the comparison of the various methods, and the selection of the best method.","abstract_html":"The survival function is defined as the probability that a person or an object will survive beyond a specified time point. It is used in many applications including human mortality. It is also known as the survivor function or reliability function. The Weibull distribution has long drawn the attention of statisticians for modeling the reliability of systems. In this thesis, making inferences for the survival function of a Weibull system which is exposed to linearly decreasing stress is of concern. The derivation of the Linearly Decreasing Stress Weibull first appears in Guenther (2014). Parameters will be estimated using maximum likelihood estimation. The approximate normality of the maximum likelihood estimate of the survival function will be studied through a small scale simulation study. Various methods for finding confidence intervals of the survival function of a Linearly Decreasing Stress Weibull system are given. A large-scale simulation study will also be conducted to study the effectiveness of the resulting confidence intervals. The simulation study will also allow for the comparison of the various methods, and the selection of the best method.","abstract_has_math":false,"creators":["Perera, Chamila Dilhani"],"institution":"Texas Tech University","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Mathematics","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":["Surles, James"],"committee_members":["Ghosh, Souparno","Ellingson, Leif"],"year":2016,"date_issued":"2016-12-01","date_published":"2016-12-01","updated_at":"2026-07-24T05:04:51Z","subjects":["Survivor function","Weibull distribution","Linearly decreasing stress Weibull","Maximum likelihood estimation","Confidence intervals"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2346/72355","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Surles, James"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Ghosh, Souparno","Ellingson, Leif"]},{"key":"dc:creator","label":"Author","values":["Perera, Chamila Dilhani"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-02-02T18:35:00Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-02-02T18:35:00Z"]},{"key":"dc:date.issued","label":"Date","values":["2016-12-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Texas Tech University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Survivor function","Weibull distribution","Linearly decreasing stress Weibull","Maximum likelihood estimation","Confidence intervals"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2346/72355"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The survival function is defined as the probability that a person or an object will survive beyond a specified time point. It is used in many applications including human mortality. It is also known as the survivor function or reliability function. The Weibull distribution has long drawn the attention of statisticians for modeling the reliability of systems. In this thesis, making inferences for the survival function of a Weibull system which is exposed to linearly decreasing stress is of concern. The derivation of the Linearly Decreasing Stress Weibull first appears in Guenther (2014). Parameters will be estimated using maximum likelihood estimation. The approximate normality of the maximum likelihood estimate of the survival function will be studied through a small scale simulation study. Various methods for finding confidence intervals of the survival function of a Linearly Decreasing Stress Weibull system are given. A large-scale simulation study will also be conducted to study the effectiveness of the resulting confidence intervals. The simulation study will also allow for the comparison of the various methods, and the selection of the best method."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Inference for the survival function of the linearly decreasing stress Weibull"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Surles, James"],"dc:contributor.committeemember":["Ghosh, Souparno","Ellingson, Leif"],"dc:creator":["Perera, Chamila Dilhani"],"dc:date.accessioned":["2017-02-02T18:35:00Z"],"dc:date.available":["2017-02-02T18:35:00Z"],"dc:date.issued":["2016-12-01"],"dc:description.abstract":["The survival function is defined as the probability that a person or an object will survive beyond a specified time point. It is used in many applications including human mortality. It is also known as the survivor function or reliability function. The Weibull distribution has long drawn the attention of statisticians for modeling the reliability of systems. In this thesis, making inferences for the survival function of a Weibull system which is exposed to linearly decreasing stress is of concern. The derivation of the Linearly Decreasing Stress Weibull first appears in Guenther (2014). Parameters will be estimated using maximum likelihood estimation. The approximate normality of the maximum likelihood estimate of the survival function will be studied through a small scale simulation study. Various methods for finding confidence intervals of the survival function of a Linearly Decreasing Stress Weibull system are given. A large-scale simulation study will also be conducted to study the effectiveness of the resulting confidence intervals. The simulation study will also allow for the comparison of the various methods, and the selection of the best method."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/2346/72355"],"dc:language.iso":["eng"],"dc:subject":["Survivor function","Weibull distribution","Linearly decreasing stress Weibull","Maximum likelihood estimation","Confidence intervals"],"dc:title":["Inference for the survival function of the linearly decreasing stress Weibull"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mathematics"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Texas Tech University"]},"updated_at":"2026-07-24T05:04:51Z"}