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Can I read Rank Estimation in Reduced-rank Regression on EtoBox?
Rank Estimation in Reduced-rank Regression by Efstathia Bura; R.Dennis Cook is a Mathematics article available to read on EtoBox.
What is Rank Estimation in Reduced-rank Regression about?
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 second moments. The test is extended to the nonconstant covariance case. Linear combinations of the components of the predictor vector that are estimated to be significant for modelling the responses are obtained.
Who reads Rank Estimation in Reduced-rank Regression?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- Efstathia Bura; R.Dennis Cook
- Publisher
- Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0047-259X)
- Published
- 2003
- Language
- EN
- Field
- Mathematics (Physical Sciences)