{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/21433"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/21433","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Model selection: Consistency and robustness properties of the Schwarz Information Criterion for generalized M-estimation","abstract":"This thesis main focus are the robustness properties of the Schwarz Information Criterion (SIC) based on sample objective functions defining (Bias) robust M-estimators. The Bayesian underpinnings of such a criterion are established by extending Schwarz's original framework to densities not belonging to the exponential family. A definition of qualitative robustness appropriate for model selection is provided and it is shown that the crucial restriction needed to achieve robustness is the uniform boundedness of the objective function defining Bias robust M-estimators. In this process, the asymptotic performance of the SIC for generalized M-estimators is also studied. The finite sample behavior of the SIC for different types of M-estimators is analyzed by means of Monte Carlo experiments.","abstract_html":"This thesis main focus are the robustness properties of the Schwarz Information Criterion (SIC) based on sample objective functions defining (Bias) robust M-estimators. The Bayesian underpinnings of such a criterion are established by extending Schwarz's original framework to densities not belonging to the exponential family. A definition of qualitative robustness appropriate for model selection is provided and it is shown that the crucial restriction needed to achieve robustness is the uniform boundedness of the objective function defining Bias robust M-estimators. In this process, the asymptotic performance of the SIC for generalized M-estimators is also studied. The finite sample behavior of the SIC for different types of M-estimators is analyzed by means of Monte Carlo experiments.","abstract_has_math":false,"creators":["Machado, Jose Antonio Ferreira"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Koenker, Roger W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T13:08:30Z","date_published":"2011-05-07T13:08:30Z","updated_at":"2026-07-22T22:25:17Z","subjects":["Statistics","Economics, Theory"],"languages":["eng"],"rights":["Copyright 1989 Machado, Jose Antonio Ferreira"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI8924813","(UMI)AAI8924813"],"render_values":[{"text":"AAI8924813","href":null,"code":true},{"text":"(UMI)AAI8924813","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/21433","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Koenker, Roger W."]},{"key":"dc:creator","label":"Author","values":["Machado, Jose Antonio Ferreira"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T13:08:30Z","10000-01-01","1989"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Statistics","Economics, Theory"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1989 Machado, Jose Antonio Ferreira"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI8924813","(UMI)AAI8924813","http://hdl.handle.net/2142/21433"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis main focus are the robustness properties of the Schwarz Information Criterion (SIC) based on sample objective functions defining (Bias) robust M-estimators. 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The Bayesian underpinnings of such a criterion are established by extending Schwarz's original framework to densities not belonging to the exponential family. A definition of qualitative robustness appropriate for model selection is provided and it is shown that the crucial restriction needed to achieve robustness is the uniform boundedness of the objective function defining Bias robust M-estimators. In this process, the asymptotic performance of the SIC for generalized M-estimators is also studied. The finite sample behavior of the SIC for different types of M-estimators is analyzed by means of Monte Carlo experiments.","Made available in DSpace on 2011-05-07T13:08:30Z (GMT). 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