Reduced rank regression assumes that the coefficient matrix in a multivariate regression model is not of full rank. The unknown rank is traditionally estimated under the assumption of normal responses. We derive an asymptotic test for the rank that only requires the response vector have finite secon
β¦ LIBER β¦
Reduced-Rank Regression and Canonical Analysis
β Scribed by M. K.-S. Tso
- Book ID
- 118176289
- Publisher
- Blackwell Publishing
- Year
- 1981
- Tongue
- English
- Weight
- 841 KB
- Volume
- 43
- Category
- Article
- ISSN
- 0035-9246
- DOI
- 10.2307/2984847
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## Abstract In previous work by Stoica and Viberg the reducedβrank regression problem is solved in a maximum likelihood sense. The present paper proposes an alternative numerical procedure. The solution is written in terms of the principal angles between subspaces spanned by the data matrices. It i
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