{"created":"2021-03-01T07:02:41.355481+00:00","id":42758,"links":{},"metadata":{"_buckets":{"deposit":"cf7b21d2-4037-4dbb-bdf0-3635dc0c90f7"},"_deposit":{"id":"42758","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42758"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042758","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2003-01","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2003-CF-190","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 consider the problem of estimating the regression parameters in a multiple linear regression model when the multicollinearity is present.Under the assumption of normality, we present three empirical Bayes estimators. One of them shrinks the least squares (LS) estimator towards the principal component. The second one is a hierarchical empirical Bayes estimator shrinking the LS estimator twice.The third one is obtained by choosing di erent priors for the two sets of regression parameters that arise in the case of multicollinearity;this estimator is termed decomposed empirical Bayes estimator. These proposed estimators are not only proved to be uniformly better than the LS estimator, that is,minimax in terms of risk under the Strawderman's loss function,but also shown to be useful in the multicollinearity cases through simulation and empirical studies.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"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/2003/2003cf190ab.html","subitem_relation_type_select":"URI"}}]},"item_8_relation_29":{"attribute_name":"異版あり","attribute_value_mlt":[{"subitem_relation_type":"hasVersion","subitem_relation_type_id":{"subitem_relation_type_id_text":"http://dx.doi.org/10.1081/STA-120037452","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":"330","subitem_subject_scheme":"NDC"}]},"item_8_text_17":{"attribute_name":"Mathmatical Subject Classification","attribute_value_mlt":[{"subitem_text_value":"62J05"},{"subitem_text_value":"62J07"},{"subitem_text_value":"62F10"},{"subitem_text_value":"62C12"},{"subitem_text_value":"62C20"}]},"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":"University of Tokyo"},{"subitem_text_value":"University of Toronto"}]},"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":"Kubokawa, Tatsuya"}],"nameIdentifiers":[{"nameIdentifier":"98327","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"M., S.  Srivastava"}],"nameIdentifiers":[{"nameIdentifier":"98328","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Multiple regression","subitem_subject_scheme":"Other"},{"subitem_subject":"multicollinearity","subitem_subject_scheme":"Other"},{"subitem_subject":"ridge regression","subitem_subject_scheme":"Other"},{"subitem_subject":"ernpirical Bayes method","subitem_subject_scheme":"Other"},{"subitem_subject":"principal component method","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":"Improved Empirical Bayes Ridge Regression Estimators under Multicollinearity","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Improved Empirical Bayes Ridge Regression Estimators under Multicollinearity"}]},"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":"42758","relation_version_is_last":true,"title":["Improved Empirical Bayes Ridge Regression Estimators under Multicollinearity"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:58.626154+00:00"}