Quadratic prediction problems in multivariate linear models

Xu-Qing Liu, Dong-Dong Wang and Jian-Ying Rong

Journal of Multivariate Analysis, 2009, vol. 100, issue 2, 291-300

Abstract: 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.

Keywords: 62M20; 62H05; 11H55; 15A09; Multivariate; linear; model; (Restricted); OIQU/OIQB; predictor; Prediction; MSE; (matrix); Permutation; matrix; Unbiasedness; Invariance; Matrix; elliptically; contoured; distribution (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (1)

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