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On the weighted least-squares, the ordinary least-squares and the best linear unbiased estimators under a restricted growth curve model

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  • Guang Jing Song
  • Qing Wen Wang

Abstract

Necessary and sufficient conditions are given for a restricted growth curve model to be consistent. The general expressions of the weighted least-squares estimators (WLSEs), the ordinary least-squares estimators (OLSEs) and the best linear unbiased estimator (BLUE) under this model are also derived. Moreover, some algebraic and statistical properties of these estimators are presented by rank method. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Guang Jing Song & Qing Wen Wang, 2014. "On the weighted least-squares, the ordinary least-squares and the best linear unbiased estimators under a restricted growth curve model," Statistical Papers, Springer, vol. 55(2), pages 375-392, May.
    • Handle: RePEc:spr:stpapr:v:55:y:2014:i:2:p:375-392
    DOI: 10.1007/s00362-012-0483-9
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    References listed on IDEAS

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    1. Yongge Tian & M. Beisiegel & E. Dagenais & C. Haines, 2008. "On the natural restrictions in the singular Gauss–Markov model," Statistical Papers, Springer, vol. 49(3), pages 553-564, July.
    2. Rao, C. Radhakrishna, 1973. "Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix," Journal of Multivariate Analysis, Elsevier, vol. 3(3), pages 276-292, September.
    3. Jürgen Groß, 2004. "The general Gauss-Markov model with possibly singular dispersion matrix," Statistical Papers, Springer, vol. 45(3), pages 311-336, July.
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    Cited by:

    1. Nenghui Kuang & Bingquan Liu, 2018. "Least squares estimator for $$\alpha $$ α -sub-fractional bridges," Statistical Papers, Springer, vol. 59(3), pages 893-912, September.

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