{"created":"2021-03-01T07:02:06.719925+00:00","id":42249,"links":{},"metadata":{"_buckets":{"deposit":"2770a6bf-5442-41e4-a522-be10be22fd67"},"_deposit":{"id":"42249","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42249"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042249","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2007-02","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-478","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":"The Snaer program calculates the posterior mean and variance of variables on some of which we have data (with precisions), on some we have prior information (with precisions), and on some prior indicator ratios (with precisions) are available. The variables must satisfy anumber of exact restrictions. The system is both large and sparse. Two aspects of the sta-tistical and computational development are a practical procedure to solve a linear integer system, and a stable linearization routine for ratios. We test our numerical method to solve large sparse linear least-squares estimation problems, and find that it performs well, even when the n ×k design matrix is large(nk equivalent 2$^{27.5}$).","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/2007/2007cf478ab.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":"334","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":"Eurandom, Eindhoven University of Technology"},{"subitem_text_value":"Tilburg University"}]},"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":"Danilov, Dmitry"}],"nameIdentifiers":[{"nameIdentifier":"97217","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Jan, R.  Magnus"}],"nameIdentifiers":[{"nameIdentifier":"97218","nameIdentifierScheme":"WEKO"}]}]},"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":"On the estimation of a large sparse Bayesian system : the Snaer program","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"On the estimation of a large sparse Bayesian system : the Snaer program"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-06-03"},"publish_date":"2013-06-03","publish_status":"0","recid":"42249","relation_version_is_last":true,"title":["On the estimation of a large sparse Bayesian system : the Snaer program"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:26.536133+00:00"}