WEKO3
アイテム
{"_buckets": {"deposit": "d5f3dda7-56fc-4aa6-ae25-889da6235bed"}, "_deposit": {"id": "37059", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "37059"}, "status": "published"}, "_oai": {"id": "oai:tsukuba.repo.nii.ac.jp:00037059", "sets": ["786", "1697", "629"]}, "item_5_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2016-03", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "199", "bibliographicPageStart": "186", "bibliographicVolumeNumber": "170", "bibliographic_titles": [{"bibliographic_title": "Journal of statistical planning and inference"}]}]}, "item_5_creator_3": {"attribute_name": "著者別名", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "矢田, 和善"}], "nameIdentifiers": [{"nameIdentifier": "204965", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "90585803", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000090585803"}, {"nameIdentifier": "0000000526", "nameIdentifierScheme": "筑波大学研究者総覧", "nameIdentifierURI": "http://trios.tsukuba.ac.jp/researcher/0000000526"}]}, {"creatorNames": [{"creatorName": "青嶋, 誠"}], "nameIdentifiers": [{"nameIdentifier": "215", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "90246679", "nameIdentifierScheme": "e-Rad", "nameIdentifierURI": "https://nrid.nii.ac.jp/ja/nrid/1000090246679"}, {"nameIdentifier": "0000000482", "nameIdentifierScheme": "筑波大学研究者総覧", "nameIdentifierURI": "http://trios.tsukuba.ac.jp/researcher/0000000482"}]}]}, "item_5_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "A common feature of high-dimensional data is that the data dimension is high, however, the sample size is relatively low. We call such data HDLSS data. In this paper, we study asymptotic properties of the first principal component in the HDLSS context and apply them to equality tests of covariance matrices for high-dimensional data sets. We consider HDLSS asymptotic theories as the dimension grows for both the cases when the sample size is fixed and the sample size goes to infinity. We introduce an eigenvalue estimator by the noise-reduction methodology and provide asymptotic distributions of the largest eigenvalue in the HDLSS context. We construct a confidence interval of the first contribution ratio and give a one-sample test. We give asymptotic properties both for the first PC direction and PC score as well. We apply the findings to equality tests of two covariance matrices in the HDLSS context. We provide numerical results and discussions about the performances both on the estimates of the first PC and the equality tests of two covariance matrices.", "subitem_description_type": "Abstract"}]}, "item_5_publisher_27": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Elsevier B.V."}]}, "item_5_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.1016/j.jspi.2015.10.007", "subitem_relation_type_select": "DOI"}}]}, "item_5_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/"}]}, "item_5_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "author"}]}, "item_5_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "0378-3758", "subitem_source_identifier_type": "ISSN"}]}, "item_5_source_id_9": {"attribute_name": "書誌レコードID", "attribute_value_mlt": [{"subitem_source_identifier": "AA00253748", "subitem_source_identifier_type": "NCID"}]}, "item_5_subject_20": {"attribute_name": "NIIサブジェクト", "attribute_value_mlt": [{"subitem_subject": "数学", "subitem_subject_scheme": "Other"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Ishii, Aki"}], "nameIdentifiers": [{"nameIdentifier": "126572", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Yata, Kazuyoshi"}], "nameIdentifiers": [{"nameIdentifier": "126573", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Aoshima, Makoto"}], "nameIdentifiers": [{"nameIdentifier": "126574", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-04-01"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "JSPI_170.pdf", "filesize": [{"value": "275.0 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_11", "mimetype": "application/pdf", "size": 275000.0, "url": {"label": "JSPI_170", "url": "https://tsukuba.repo.nii.ac.jp/record/37059/files/JSPI_170.pdf"}, "version_id": "b68e3238-dd91-40e4-b41c-b42a9a069efa"}]}, "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": "Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context"}]}, "item_type_id": "5", "owner": "1", "path": ["786", "1697", "629"], "permalink_uri": "http://hdl.handle.net/2241/00135107", "pubdate": {"attribute_name": "公開日", "attribute_value": "2016-02-15"}, "publish_date": "2016-02-15", "publish_status": "0", "recid": "37059", "relation": {}, "relation_version_is_last": true, "title": ["Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context"], "weko_shared_id": 5}
Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context
http://hdl.handle.net/2241/00135107
http://hdl.handle.net/2241/00135107d13f9674-2523-462f-bbb4-3eb432481e7e
名前 / ファイル | ライセンス | アクション |
---|---|---|
JSPI_170 (275.0 kB)
|
Item type | Journal Article(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2016-02-15 | |||||
タイトル | ||||||
タイトル | Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Ishii, Aki
× Ishii, Aki× Yata, Kazuyoshi× Aoshima, Makoto |
|||||
著者別名 |
矢田, 和善
× 矢田, 和善× 青嶋, 誠 |
|||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | A common feature of high-dimensional data is that the data dimension is high, however, the sample size is relatively low. We call such data HDLSS data. In this paper, we study asymptotic properties of the first principal component in the HDLSS context and apply them to equality tests of covariance matrices for high-dimensional data sets. We consider HDLSS asymptotic theories as the dimension grows for both the cases when the sample size is fixed and the sample size goes to infinity. We introduce an eigenvalue estimator by the noise-reduction methodology and provide asymptotic distributions of the largest eigenvalue in the HDLSS context. We construct a confidence interval of the first contribution ratio and give a one-sample test. We give asymptotic properties both for the first PC direction and PC score as well. We apply the findings to equality tests of two covariance matrices in the HDLSS context. We provide numerical results and discussions about the performances both on the estimates of the first PC and the equality tests of two covariance matrices. | |||||
書誌情報 |
Journal of statistical planning and inference 巻 170, p. 186-199, 発行日 2016-03 |
|||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0378-3758 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA00253748 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1016/j.jspi.2015.10.007 | |||||
権利 | ||||||
権利情報 | © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | Elsevier B.V. |