Journal of East China Normal University(Natural Sc ›› 2008, Vol. 2008 ›› Issue (5): 66-71,1.

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Balanced generalized LS estimation of the regressive coefficient

QIU Hong-bing1, LUO Ji2,3   

  1. 1. Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou 510006, China; 2. School of Finance and Statistics, East China Normal University, Shanghai 200062, China;3. School of Mathematics and Statistics, Zhejiang University of Finance and Economics, Hangzhou 310018, China
  • Received:2008-03-15 Revised:2008-06-03 Online:2008-09-25 Published:2008-09-25
  • Contact: LUO Ji

Abstract:

Based on the idea of balanced loss function, a new measuring standard for the estimations of uperiorities was proposed for general linear models. Under the new standard, the balanced generalized LS estimation of the regressive coefficient was derived. The necessary and sufficient condition for its unbiasedness was discussed and its superiority over BLUE in terms of the mean square error matrix criterion was studied.

Key words: parameter estimation, mean square error matrix criterion, balanced LS estimation, best linear unbiased estimation, linear model, parameter estimation, mean square error matrix criterion, balanced LS estimation, best linear unbiased estimation

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