<b>A RESTRAINED CONDITION NUMBER LEAST SQUARES TECHNIQUE WITH ITS APPLICATIONS TO AVOIDING </b><b>RANK DEFICIENCY</b>

• Adachi Kohei

  Graduate School of Human Sciences, Osaka University

書誌事項

タイトル別名

• <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

抄録

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

• Ｊｏｕｒｎａｌ　ｏｆ　ｔｈｅ　Ｊａｐａｎｅｓｅ　Ｓｏｃｉｅｔｙ　ｏｆ　Ｃｏｍｐｕｔａｔｉｏｎａｌ　Ｓｔａｔｉｓｔｉｃｓ

  Ｊｏｕｒｎａｌ　ｏｆ　ｔｈｅ　Ｊａｐａｎｅｓｅ　Ｓｏｃｉｅｔｙ　ｏｆ　Ｃｏｍｐｕｔａｔｉｏｎａｌ　Ｓｔａｔｉｓｔｉｃｓ 26 (1), 39-51, 2013

  日本計算機統計学会

キーワード

• Constrained least squares
• Condition number
• Rank preserving
• Singular value decomposition
• Reverse component analysis
• Oblique Procrustes rotation
• PARAFAC

詳細情報

• CRID: 1390001204416084736
• NII論文ID: 130004842780
• NII書誌ID: AA10823693
• DOI: 10.5183/jjscs.1208002_201
• ISSN: 18811337
• ISSN: 09152350
• NDL書誌ID: 030632943
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I030632943
• 本文言語コード: en
• データソース種別:
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  • NDL
  • Crossref
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  • KAKEN
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