WEKO3
アイテム
{"_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": ["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_text": "https://hyokadb02.jimu.kyutech.ac.jp/html/241_ja.html", "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": [{"familyName": "Hirose", "familyNameLang": "en"}, {"familyName": "廣瀬", "familyNameLang": "ja"}, {"familyName": "ヒロセ", "familyNameLang": "ja-Kana"}], "givenNames": [{"givenName": "Hideo", "givenNameLang": "en"}, {"givenName": "英雄", "givenNameLang": "ja"}, {"givenName": "ヒデオ", "givenNameLang": "ja-Kana"}], "nameIdentifiers": [{"nameIdentifier": "879", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "60275401", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000060275401"}, {"nameIdentifier": "56153010700", "nameIdentifierScheme": "Scopus著者ID", "nameIdentifierURI": "https://www.scopus.com/authid/detail.uri?authorId=56153010700"}]}, {"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": [{"familyName": "Komori", "familyNameLang": "en"}, {"familyName": "小守", "familyNameLang": "ja"}, {"familyName": "コモリ", "familyNameLang": "ja-Kana"}], "givenNames": [{"givenName": "Yoshio", "givenNameLang": "en"}, {"givenName": "良雄", "givenNameLang": "ja"}, {"givenName": "ヨシオ", "givenNameLang": "ja-Kana"}], "nameIdentifiers": [{"nameIdentifier": "3142", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "20285430", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000020285430"}, {"nameIdentifier": "7101844227", "nameIdentifierScheme": "Scopus著者ID", "nameIdentifierURI": "https://www.scopus.com/authid/detail.uri?authorId=7101844227"}, {"nameIdentifier": "241", "nameIdentifierScheme": "九工大研究者情報", "nameIdentifierURI": "https://hyokadb02.jimu.kyutech.ac.jp/html/241_ja.html"}]}]}, "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", "download_preview_message": "", "file_order": 0, "filename": "csse-17.pdf", "filesize": [{"value": "100.8 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 100800.0, "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"], "permalink_uri": "http://hdl.handle.net/10228/5323", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2015-01-08"}, "publish_date": "2015-01-08", "publish_status": "0", "recid": "4112", "relation": {}, "relation_version_is_last": true, "title": ["Maximum likelihood estimation in a mixture regression model using the EM algorithm"], "weko_shared_id": -1}
Maximum likelihood estimation in a mixture regression model using the EM algorithm
http://hdl.handle.net/10228/5323
http://hdl.handle.net/10228/53231e3d8737-ec0a-4a7e-b572-2a3e7513ab5e
名前 / ファイル | ライセンス | アクション |
---|---|---|
csse-17.pdf (100.8 kB)
|
|
Item type | テクニカルレポート = Technical Report(1) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
公開日 | 2015-01-08 | |||||||||||
資源タイプ | ||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||||||
資源タイプ | technical report | |||||||||||
タイトル | ||||||||||||
言語 | en | |||||||||||
タイトル | Maximum likelihood estimation in a mixture regression model using the EM algorithm | |||||||||||
言語 | ||||||||||||
言語 | eng | |||||||||||
著者 |
廣瀬, 英雄
× 廣瀬, 英雄× 小守, 良雄
WEKO
3142
|
|||||||||||
抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | 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. | |||||||||||
言語 | en | |||||||||||
書誌情報 |
en : Technical Report in Computer Science and Systems Engineering p. 1-15, 発行日 2002 |
|||||||||||
出版社 | ||||||||||||
言語 | ja | |||||||||||
出版者 | 九州工業大学 | |||||||||||
ISSN | ||||||||||||
収録物識別子タイプ | PISSN | |||||||||||
収録物識別子 | 1344-8803 | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Newton-Raphson | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | simplex method | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | power-law | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Weibull distribution | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Weibull-power-law | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | EM algorithm | |||||||||||
出版タイプ | ||||||||||||
出版タイプ | VoR | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
テクニカルレポートNo. | ||||||||||||
CSSE-17 | ||||||||||||
研究者情報 | ||||||||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/241_ja.html | ||||||||||||
連携ID | ||||||||||||
5045 |