{"created":"2021-03-01T07:02:46.600975+00:00","id":42835,"links":{},"metadata":{"_buckets":{"deposit":"bafd28b5-20a5-4a65-ade5-2398005fc384"},"_deposit":{"id":"42835","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42835"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042835","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2012-12","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-872","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-F"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, we suggest the new variable selection procedure, called MEC, for linear discriminant rule in the high-dimensional setup. MEC is derived as a second-order unbiased estimator of the misclassification error probability of the linear discriminant rule. It is shown that MEC not only decomposes into 'fitting'and 'penalty'terms like AIC and Mallows Cp, but also possesses an asymptotic optimality in the sense that MEC achieves the smallest possible conditional probability of misclassification in candidate variable sets. Through simulation studies, it is shown that MEC has good performances in the sense of selecting the true variable sets.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"Revised in February 2013.","subitem_description_type":"Other"},{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2012/2012cf872ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11450569","subitem_source_identifier_type":"NCID"}]},"item_8_subject_15":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"335","subitem_subject_scheme":"NDC"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Faculty of Economics, University of Tokyo"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hyodo, Masashi"}],"nameIdentifiers":[{"nameIdentifier":"98477","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Kubokawa, Tatsuya"}],"nameIdentifiers":[{"nameIdentifier":"98478","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"asymptotic optimality","subitem_subject_scheme":"Other"},{"subitem_subject":"high dimension","subitem_subject_scheme":"Other"},{"subitem_subject":"linear discriminant analysis","subitem_subject_scheme":"Other"},{"subitem_subject":"misclassification error","subitem_subject_scheme":"Other"},{"subitem_subject":"multivariate normal","subitem_subject_scheme":"Other"},{"subitem_subject":"second-order approximation","subitem_subject_scheme":"Other"},{"subitem_subject":"variable selection","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"A Variable Selection Criterion for Linear Discriminant Rule and its Optimality in High Dimensional Setting","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A Variable Selection Criterion for Linear Discriminant Rule and its Optimality in High Dimensional Setting"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-01-17"},"publish_date":"2017-01-17","publish_status":"0","recid":"42835","relation_version_is_last":true,"title":["A Variable Selection Criterion for Linear Discriminant Rule and its Optimality in High Dimensional Setting"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:18:00.443178+00:00"}