Statistical Papers

, Volume 51, Issue 2, pp 315–323

A new stochastic mixed ridge estimator in linear regression model

Note

DOI: 10.1007/s00362-008-0169-5

Cite this article as:
Li, Y. & Yang, H. Stat Papers (2010) 51: 315. doi:10.1007/s00362-008-0169-5

Abstract

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.

Keywords

Ordinary ridge estimatorOrdinary mixed estimatorStochastic mixed ridge estimatorMean squared error matrix

Mathematics Subject Classification (2000)

62J0562F30

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department of Statistics and Actuarial ScienceChongqing UniversityChongqingChina