<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
Bibliographic Information
- Other Title
-
- <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
Search this article
Abstract
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.
Journal
-
- Journal of the Japanese Society of Computational Statistics
-
Journal of the Japanese Society of Computational Statistics 26 (1), 39-51, 2013
Japanese Society of Computational Statistics
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390001204416084736
-
- NII Article ID
- 130004842780
-
- NII Book ID
- AA10823693
-
- ISSN
- 18811337
- 09152350
-
- NDL BIB ID
- 030632943
-
- Text Lang
- en
-
- Data Source
-
- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed