Quadratic prediction problems in multivariate linear models
Linear and quadratic prediction problems in finite populations have become of great interest to many authors recently. In the present paper, we mainly aim to extend the problem of quadratic prediction from a general linear model, of form , to a multivariate linear model, denoted by with . Firstly, the optimal invariant quadratic unbiased (OIQU) predictor and the optimal invariant quadratic (potentially) biased (OIQB) predictor of for any particular symmetric nonnegative definite matrix satisfying are derived. Secondly, we consider predicting and . The corresponding restricted OIQU predictor and restricted OIQB predictor for them are given. In addition, we also offer four concluding remarks. One concerns the generalization of predicting and , and the others are concerned with three possible extensions from multivariate linear models to growth curve models, to restricted multivariate linear models, and to matrix elliptical linear models.
Year of publication: |
2009
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Authors: | Liu, Xu-Qing ; Wang, Dong-Dong ; Rong, Jian-Ying |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 2, p. 291-300
|
Publisher: |
Elsevier |
Keywords: | 62M20 62H05 11H55 15A09 Multivariate linear model (Restricted) OIQU/OIQB predictor Prediction MSE (matrix) Permutation matrix Unbiasedness Invariance Matrix elliptically contoured distribution |
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