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
Stochastic complexities of reduced rank regression in Bayesian estimation
β Scribed by Miki Aoyagi; Sumio Watanabe
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 177 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0893-6080
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