<b>A RESTRAINED CONDITION NUMBER LEAST SQUARES TECHNIQUE WITH ITS APPLICATIONS TO AVOIDING </b><b>RANK DEFICIENCY</b>
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- Adachi Kohei
- Graduate School of Human Sciences, Osaka University
書誌事項
- タイトル別名
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- <b>A RESTRAINED CONDITION NUMBER LEAST SQUARES TECHNIQUE WITH ITS APPLICATIONS TO AVOIDING </b><b>RANK DEFICIENCY </b>
- A RESTRAINED CONDITION NUMBER LEAST SQUARES TECHNIQUE WITH ITS APPLICATIONS TO AVOIDING RANK DEFICIENCY
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説明
ABSTRACT An algorithm for the constrained least squares problem is proposed in which the upper bound of the condition number of a parameter matrix is predetermined. Inthe algorithm, the parameter matrix to be obtained is reparameterized using its sin gular value decomposition, and the loss function is minimized alternately over the singular vector matrices and the singular values with condition number constraint. It was demonstrated that the algorithm recovered full rank matrices in simulated reverse component analysis, in which the matrices were estimated from their reduced rank counterparts. The proposed algorithm is useful for avoiding degenerate solutions in which parameter matrices become rank decient, which is illustrated in its application to generalized oblique Procrustes rotation and three-mode Parafac component analysis.
収録刊行物
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- Journal of the Japanese Society of Computational Statistics
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Journal of the Japanese Society of Computational Statistics 26 (1), 39-51, 2013
日本計算機統計学会
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詳細情報 詳細情報について
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- CRID
- 1390001204416084736
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- NII論文ID
- 130004842780
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- NII書誌ID
- AA10823693
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- ISSN
- 18811337
- 09152350
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- NDL書誌ID
- 030632943
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可