Abstract
The envelope model recently developed for the classical multivariate linear regression have potential gain in efficiency in estimating unknown parameters over usual maximum likelihood estimation. In this paper, we theoretically investigate the envelope model as dimension reduction for response variables and connect them to existing methods.
Original language | English |
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Pages (from-to) | 143-148 |
Number of pages | 6 |
Journal | Journal of the Korean Statistical Society |
Volume | 42 |
Issue number | 2 |
DOIs | |
State | Published - Jun 2013 |
Bibliographical note
Funding Information:This work was supported by Basic Science Research Program through the National Research Foundation of Korea (KRF) funded by the Ministry of Education, Science and Technology (2011-0005581).
Keywords
- Envelope model
- Multivariate linear regression
- Reducing subspaces
- Response dimension reduction