{"created":"2023-05-15T08:43:45.500717+00:00","id":8846,"links":{},"metadata":{"_buckets":{"deposit":"2f6a8ff8-c558-4ce2-9880-fa1ac3fa603b"},"_deposit":{"created_by":13,"id":"8846","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"8846"},"status":"published"},"_oai":{"id":"oai:uec.repo.nii.ac.jp:00008846","sets":["6"]},"author_link":["24019","24022","24021","24020"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-11-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"16","bibliographicPageEnd":"4153","bibliographicPageStart":"4132","bibliographicVolumeNumber":"48","bibliographic_titles":[{},{"bibliographic_title":"Communications in Statistics - Theory and Methods","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The fused lasso penalizes a loss function by the L1 norm for both the regression coefficients and their successive differences to encourage sparsity of both. In this paper, we propose a Bayesian generalized fused lasso modeling based on a normal-exponential-gamma (NEG) prior distribution. The NEG prior is assumed into the difference of successive regression coefficients. The proposed method enables us to construct a more versatile sparse model than the ordinary fused lasso using a flexible regularization term. Simulation studies and real data analyses show that the proposed method has superior performance to the ordinary fused lasso.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Taylor & Francis"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1080/03610926.2018.1489056","subitem_relation_type_select":"DOI"}}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1080/03610926.2018.1489056","subitem_relation_type_select":"DOI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 2019 available online: http://www.tandfonline.com/10.1080/03610926.2018.1489056 "}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0361-0926","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shimamura, Kaito","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ueki, Masao","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kawano, Shuichi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Konishi, Sadanori","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-11-17"}],"displaytype":"detail","filename":"ShimamuraEtAl.pdf","filesize":[{"value":"611.8 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"ShimamuraEtAl","url":"https://uec.repo.nii.ac.jp/record/8846/files/ShimamuraEtAl.pdf"},"version_id":"ac1f10b0-acb5-41b7-bf60-33237dc0b866"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Bayesian lasso","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Bayesian model","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"hierarchical normal-exponential-gamma distribution","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Markov chain Monte Carlo","subitem_subject_language":"en","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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Bayesian generalized fused lasso modeling via NEG distribution","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Bayesian generalized fused lasso modeling via NEG distribution","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"13","path":["6"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-01-11"},"publish_date":"2019-01-11","publish_status":"0","recid":"8846","relation_version_is_last":true,"title":["Bayesian generalized fused lasso modeling via NEG distribution"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2023-05-15T10:13:47.186042+00:00"}