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A derivation of BLUP--Best linear unbiased predictor

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  • Jiang, Jiming

Abstract

We show the best linear unbiased predictor (BLUP) can be derived as the best predictor (under normality) based on all error contrasts (i.e., transformation of data with mean 0). The result reveals an interesting connection between BLUP and REML--restricted or residual maximum likelihood--estimates.

Suggested Citation

  • Jiang, Jiming, 1997. "A derivation of BLUP--Best linear unbiased predictor," Statistics & Probability Letters, Elsevier, vol. 32(3), pages 321-324, March.
    • Handle: RePEc:eee:stapro:v:32:y:1997:i:3:p:321-324
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    Cited by:

    1. Eduardo Minuci & Scott Schuh, 2022. "Are West Virginia Banks Unique?," Working Papers 22-03, Department of Economics, West Virginia University.
    2. Pouliot, Guillaume Allaire, 2023. "Spatial econometrics for misaligned data," Journal of Econometrics, Elsevier, vol. 232(1), pages 168-190.
    3. 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.
    4. Guillaume Allaire Pouliot, 2022. "Spatial Econometrics for Misaligned Data," Papers 2207.04082, arXiv.org.

    More about this item

    Keywords

    Mixed models Error contrasts REML;

    Statistics

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