Statistical Papers

, Volume 51, Issue 2, pp 315–323 | Cite as

A new stochastic mixed ridge estimator in linear regression model

  • Yalian Li
  • Hu YangEmail author


This paper is concerned with the parameter estimation in linear regression model with additional stochastic linear restrictions. To overcome the multicollinearity problem, a new stochastic mixed ridge estimator is proposed and its efficiency is discussed. Necessary and sufficient conditions for the superiority of the stochastic mixed ridge estimator over the ridge estimator and the mixed estimator in the mean squared error matrix sense are derived for the two cases in which the parametric restrictions are correct and are not correct. Finally, a numerical example is also given to show the theoretical results.


Ordinary ridge estimator Ordinary mixed estimator Stochastic mixed ridge estimator Mean squared error matrix 

Mathematics Subject Classification (2000)

62J05 62F30 


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department of Statistics and Actuarial ScienceChongqing UniversityChongqingChina

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