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On simultaneous prediction in a multivariate general linear model with future observations

Author

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  • Tian, Yongge
  • Wang, Cheng

Abstract

We provide a general derivation for the closed-form formula of the best linear unbiased predictors (BLUPs) of all unknown parameter matrices in a multivariate general linear model (MGLM) with future observations by using some new matrix analysis tools, and present a variety of valuable properties and features of the BLUPs under various general assumptions.

Suggested Citation

  • Tian, Yongge & Wang, Cheng, 2017. "On simultaneous prediction in a multivariate general linear model with future observations," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 52-59.
    • Handle: RePEc:eee:stapro:v:128:y:2017:i:c:p:52-59
    DOI: 10.1016/j.spl.2017.04.007
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    References listed on IDEAS

    as
    1. Shengjun Gan & Yuqin Sun & Yongge Tian, 2017. "Equivalence of predictors under real and over-parameterized linear models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(11), pages 5368-5383, June.
    2. Yongge Tian, 2015. "A new derivation of BLUPs under random-effects model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(8), pages 905-918, November.
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