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Best linear unbiased prediction for linear combinations in general mixed linear models

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  • Liu, Xu-Qing
  • Rong, Jian-Ying
  • Liu, Xiu-Ying

Abstract

The general mixed linear model can be written as . In this paper, we mainly deal with two problems. Firstly, the problem of predicting a general linear combination of fixed effects and realized values of random effects in a general mixed linear model is considered and an explicit representation of the best linear unbiased predictor (BLUP) is derived. In addition, we apply the resulting conclusion to several special models and offer an alternative to characterization of BLUP. Secondly, we recall the notion of linear sufficiency and consider it as regards the BLUP problem and characterize it in several different ways. Further, we study the concepts of linear sufficiency, linear minimal sufficiency and linear completeness, and give relations among them. Finally, four concluding remarks are given.

Suggested Citation

  • Liu, Xu-Qing & Rong, Jian-Ying & Liu, Xiu-Ying, 2008. "Best linear unbiased prediction for linear combinations in general mixed linear models," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1503-1517, September.
    • Handle: RePEc:eee:jmvana:v:99:y:2008:i:8:p:1503-1517
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    References listed on IDEAS

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    1. Heiligers, Berthold & Markiewicz, Augustyn, 1996. "Linear sufficiency and admissibility in restricted linear models," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 105-111, October.
    2. Ibarrola, P. & Pérez-Palomares, A., 2003. "Linear sufficiency and linear admissibility in a continuous time Gauss-Markov model," Journal of Multivariate Analysis, Elsevier, vol. 87(2), pages 315-327, November.
    3. Drygas, Hilmar, 1985. "Linear sufficiency and some applications in multilinear estimation," Journal of Multivariate Analysis, Elsevier, vol. 16(1), pages 71-84, February.
    4. Mueller, Jochen, 1987. "Sufficiency and completeness in the linear model," Journal of Multivariate Analysis, Elsevier, vol. 21(2), pages 312-323, April.
    5. Markiewicz, Augustyn, 1998. "Comparison of linear restricted models with respect to the validity of admissible and linearly sufficient estimators," Statistics & Probability Letters, Elsevier, vol. 38(4), pages 347-354, July.
    6. Liu, Xu-qing & Rong, Jian-ying, 2007. "Nonnegative quadratic estimation and quadratic sufficiency in general linear models," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1180-1194, July.
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    Cited by:

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    2. Nesrin Güler & Melek Eriş Büyükkaya & Melike Yiğit, 2022. "Comparison of Covariance Matrices of Predictors in Seemingly Unrelated Regression Models," Indian Journal of Pure and Applied Mathematics, Springer, vol. 53(3), pages 801-809, September.
    3. Dermoune, Azzouz & Rahmania, Nadji & Wei, Tianwen, 2012. "General linear mixed model and signal extraction problem with constraint," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 311-321.
    4. S. J. Haslett & X. Q. Liu & A. Markiewicz & S. Puntanen, 2020. "Some properties of linear sufficiency and the BLUPs in the linear mixed model," Statistical Papers, Springer, vol. 61(1), pages 385-401, February.
    5. Shu Ming YANG & Su Hua ZHANG & Tao YANG & Li WANG, 2018. "Detection of QTLs for cold tolerance at the booting stage in near-isogenic lines derived from rice landrace Lijiangxintuanheigu," Czech Journal of Genetics and Plant Breeding, Czech Academy of Agricultural Sciences, vol. 54(3), pages 93-100.
    6. Xiaojun Shi & Hiroshi Tsuji & Shunming Zhang, 2012. "Introducing Heterogeneity of Managers' Attitude into Behavioral Risk Scoring for Software Offshoring," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(3), pages 299-316, May.
    7. 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.
    8. Liu, Xin & Wang, Qing-Wen, 2013. "Equality of the BLUPs under the mixed linear model when random components and errors are correlated," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 297-309.
    9. Laura M. Grajeda & Lisa M. Thompson & William Arriaga & Eduardo Canuz & Saad B. Omer & Michael Sage & Eduardo Azziz-Baumgartner & Joe P. Bryan & John P. McCracken, 2020. "Effectiveness of Gas and Chimney Biomass Stoves for Reducing Household Air Pollution Pregnancy Exposure in Guatemala: Sociodemographic Effect Modifiers," IJERPH, MDPI, vol. 17(21), pages 1-14, October.
    10. Liu, Xu-Qing & Wang, Dong-Dong & Rong, Jian-Ying, 2009. "Quadratic prediction and quadratic sufficiency in finite populations," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1979-1988, October.

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