Abstract
Reduced rank approximation of matrices has hitherto been possible only by unweighted least squares. This paper presents iterative techniques for obtaining such approximations when weights are introduced. The techniques involve criss-cross regressions with careful initialization. Possible applications of the approximation are in modelling, biplotting, contingency table analysis, fitting of missing values, checking outliers, etc.
Original language | English |
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Pages (from-to) | 489-498 |
Number of pages | 10 |
Journal | Technometrics |
Volume | 21 |
Issue number | 4 |
DOIs | |
State | Published - Nov 1979 |
Keywords
- Biplot
- Contingency table
- Criss-cross regression
- Householder-Young theorem
- Least squares
- Outliers
- Reduced rank approximation