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Inference on High-Dimensional Mean Vectors with Fewer Observations Than the Dimension
http://hdl.handle.net/2241/117757
http://hdl.handle.net/2241/11775786bf46f7-2d90-469f-a060-8ba5f49c9f87
名前 / ファイル | ライセンス | アクション |
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MCAP_14-3.pdf (171.2 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2012-11-08 | |||||
タイトル | ||||||
タイトル | Inference on High-Dimensional Mean Vectors with Fewer Observations Than the Dimension | |||||
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 |
Yata, Kazuyoshi
× Yata, Kazuyoshi× Aoshima, Makoto |
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著者別名 |
矢田, 和善
× 矢田, 和善× 青嶋, 誠 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | We focus on inference about high-dimensional mean vectors when the sample size is much fewer than the dimension. Such data situation occurs in many areas of modern science such as genetic microarrays, medical imaging, text recognition, finance, chemometrics, and so on. First, we give a given-radius confidence region for mean vectors. This inference can be utilized as a variable selection of high-dimensional data. Next, we give a given-width confidence interval for squared norm of mean vectors. This inference can be utilized in a classification procedure of high-dimensional data. In order to assure a prespecified coverage probability, we propose a two-stage estimation methodology and determine the required sample size for each inference. Finally, we demonstrate how the new methodologies perform by using a microarray data set. | |||||
書誌情報 |
Methodology and computing in applied probability 巻 14, 号 3, p. 459-476, 発行日 2012-09 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1387-5841 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11603171 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1007/s11009-011-9233-z | |||||
権利 | ||||||
権利情報 | © Springer Science + Business Media, LLC 2011 The original publication is available at www.springerlink.com | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | Springer US | |||||
URI | ||||||
識別子 | http://hdl.handle.net/2241/117757 | |||||
識別子タイプ | HDL |