{"created":"2021-03-01T07:03:18.376981+00:00","id":25203,"links":{},"metadata":{"_buckets":{"deposit":"ecfb5d9e-e97b-4d7d-b90f-7fc84506be5c"},"_deposit":{"created_by":290,"id":"25203","owners":[290],"pid":{"revision_id":0,"type":"depid","value":"25203"},"status":"published"},"_oai":{"id":"oai:tsukuba.repo.nii.ac.jp:00025203","sets":["3:62:1722555831928"]},"author_link":[],"item_1644910766877":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_1722561470159":{"attribute_name":"著者情報","attribute_value_mlt":[{"subitem_link_text":"数理物質系; 矢田, 和善; ヤタ, カズヨシ; YATA, Kazuyoshi","subitem_link_url":"http://trios.tsukuba.ac.jp/researcher/0000000526"},{"subitem_link_text":"数理物質系; 青嶋, 誠; アオシマ, マコト; AOSHIMA, Makoto","subitem_link_url":"http://trios.tsukuba.ac.jp/researcher/0000000482"}]},"item_5_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2012-02","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"215","bibliographicPageStart":"193","bibliographicVolumeNumber":"105","bibliographic_titles":[{"bibliographic_title":"Journal of multivariate analysis","bibliographic_titleLang":"en"}]}]},"item_5_publisher_27":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Elsevier","subitem_publisher_language":"en"}]},"item_5_relation_11":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1016/j.jmva.2011.09.002","subitem_relation_type_select":"DOI"}}]},"item_5_rights_12":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"© 2011 Elsevier Inc.","subitem_rights_language":"en"},{"subitem_rights":"NOTICE: this is the author's version of a work that was accepted for publication in Journal of Multivariate Analysis. Changes resulting from the publishing process such as peer review editing corrections structural formatting and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Multivariate Analysis Vol.105 Issue 1 Pages:193-215. doi: 10.1016/j.jmva.2011.09.002","subitem_rights_language":"en"}]},"item_5_source_id_7":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0047-259X","subitem_source_identifier_type":"PISSN"}]},"item_5_source_id_9":{"attribute_name":"NCID","attribute_value_mlt":[{"subitem_source_identifier":"AA0025295X","subitem_source_identifier_type":"NCID"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"YATA Kazuyoshi","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"AOSHIMA Makoto","creatorNameLang":"en"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2013-12-25"}],"displaytype":"detail","filename":"JMA_105-1.pdf","filesize":[{"value":"749.6 kB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://tsukuba.repo.nii.ac.jp/record/25203/files/JMA_105-1.pdf"},"version_id":"610d22f9-11fb-4a17-afe9-2ef06c5263b7"}]},"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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Effective PCA for high-dimension low-sample-size data with noise reduction via geometric representations","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Effective PCA for high-dimension low-sample-size data with noise reduction via geometric representations","subitem_title_language":"en"}]},"item_type_id":"5","owner":"290","path":["1722555831928"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2011-10-11"},"publish_date":"2011-10-11","publish_status":"0","recid":"25203","relation_version_is_last":true,"title":["Effective PCA for high-dimension low-sample-size data with noise reduction via geometric representations"],"weko_creator_id":"290","weko_shared_id":-1},"updated":"2025-06-05T23:38:59.039156+00:00"}