{"created":"2021-03-01T07:01:55.696693+00:00","id":42087,"links":{},"metadata":{"_buckets":{"deposit":"a49b5e16-e839-4c46-975f-5c397df0f60f"},"_deposit":{"id":"42087","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42087"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042087","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2008-09","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-594","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":"Tobit models are extended to allow threshold values which depend on individuals'characteristics. In such models, the parameters are subject to as many inequality constraints as the number of observations, and the maximum likelihood estimation which requires the numerical maximisation of the likelihood is often difficult to be implemented. Using a Bayesian approach, a Gibbs sampler algorithm is proposed and, further, the convergence to the posterior distribution is accelerated by introducing an additional scale transformation step. The procedure is illustrated using the simulated data, wage data and prime rate changes data.","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/2008/2008cf594ab.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":"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":"Omori, Yasuhiro"}],"nameIdentifiers":[{"nameIdentifier":"96852","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Koji, Miyawaki"}],"nameIdentifiers":[{"nameIdentifier":"96853","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Bayesian analysis","subitem_subject_scheme":"Other"},{"subitem_subject":"Censored regression model","subitem_subject_scheme":"Other"},{"subitem_subject":"Markov chain Monte Carlo","subitem_subject_scheme":"Other"},{"subitem_subject":"Sample selection model","subitem_subject_scheme":"Other"},{"subitem_subject":"Tobit model","subitem_subject_scheme":"Other"},{"subitem_subject":"Unknown censoring threshold","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":"Tobit Model with Covariate Dependent Thresholds","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Tobit Model with Covariate Dependent Thresholds"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-05-31"},"publish_date":"2013-05-31","publish_status":"0","recid":"42087","relation_version_is_last":true,"title":["Tobit Model with Covariate Dependent Thresholds"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:22.484969+00:00"}