{"created":"2023-05-15T11:58:11.461311+00:00","id":4112,"links":{},"metadata":{"_buckets":{"deposit":"7cf2ad84-b880-444a-a192-8ea72e9b8359"},"_deposit":{"created_by":14,"id":"4112","owners":[14],"pid":{"revision_id":0,"type":"depid","value":"4112"},"status":"published"},"_oai":{"id":"oai:kyutech.repo.nii.ac.jp:00004112","sets":["12:19"]},"author_link":["879","3142"],"item_24_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2002","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"15","bibliographicPageStart":"1","bibliographic_titles":[{"bibliographic_title":"Technical Report in Computer Science and Systems Engineering","bibliographic_titleLang":"en"}]}]},"item_24_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"To an extremely difficult problem of finding the maximum likelihood estimates in a specific mixture regression model, a combination of several optimization techniques is found to be useful. These algorithms are the continuation method, Newton-Raphson method, and simplex method. The simplex method finds a globally approximate solution, then a combination of the continuation method and the Newton-Raphson method finds a more accurate solution. In this paper, this combination method is applied to find the maximum likelihood estimates in a Weibull-power-law type regression model, as well as the well-known methods like the EM algorithm, is discussed in this paper.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_24_link_61":{"attribute_name":"研究者情報","attribute_value_mlt":[{"subitem_link_url":"https://hyokadb02.jimu.kyutech.ac.jp/html/241_ja.html"}]},"item_24_publisher_7":{"attribute_name":"出版社","attribute_value_mlt":[{"subitem_publisher":"九州工業大学","subitem_publisher_language":"ja"}]},"item_24_source_id_8":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1344-8803","subitem_source_identifier_type":"PISSN"}]},"item_24_text_58":{"attribute_name":"テクニカルレポートNo.","attribute_value_mlt":[{"subitem_text_value":"CSSE-17"}]},"item_24_text_62":{"attribute_name":"連携ID","attribute_value_mlt":[{"subitem_text_value":"5045"}]},"item_24_version_type_59":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hirose, Hideo","creatorNameLang":"en"},{"creatorName":"廣瀬, 英雄","creatorNameLang":"ja"},{"creatorName":"ヒロセ, ヒデオ","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{},{}]},{"creatorAffiliations":[{"affiliationNames":[{"affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"Komori, Yoshio","creatorNameLang":"en"},{"creatorName":"小守, 良雄","creatorNameLang":"ja"},{"creatorName":"コモリ, ヨシオ","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{},{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2015-01-08"}],"displaytype":"detail","filename":"csse-17.pdf","filesize":[{"value":"100.8 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"csse-17.pdf","url":"https://kyutech.repo.nii.ac.jp/record/4112/files/csse-17.pdf"},"version_id":"90edf1f5-5172-44cd-99ef-905ffccdf2c3"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Newton-Raphson","subitem_subject_scheme":"Other"},{"subitem_subject":"simplex method","subitem_subject_scheme":"Other"},{"subitem_subject":"power-law","subitem_subject_scheme":"Other"},{"subitem_subject":"Weibull distribution","subitem_subject_scheme":"Other"},{"subitem_subject":"Weibull-power-law","subitem_subject_scheme":"Other"},{"subitem_subject":"EM algorithm","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":"Maximum likelihood estimation in a mixture regression model using the EM algorithm","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Maximum likelihood estimation in a mixture regression model using the EM algorithm","subitem_title_language":"en"}]},"item_type_id":"24","owner":"14","path":["19"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2015-01-08"},"publish_date":"2015-01-08","publish_status":"0","recid":"4112","relation_version_is_last":true,"title":["Maximum likelihood estimation in a mixture regression model using the EM algorithm"],"weko_creator_id":"14","weko_shared_id":-1},"updated":"2023-11-20T01:34:54.625346+00:00"}