Statistical Papers

, Volume 60, Issue 5, pp 1717–1739 | Cite as

Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models

  • Fikri AkdenizEmail author
  • Mahdi Roozbeh
Regular Article


In this paper, a generalized difference-based estimator is introduced for the vector parameter \(\beta \) in partially linear model when the errors are correlated. A generalized difference-based almost unbiased ridge estimator is defined for the vector parameter \(\beta \). Under the linear stochastic constraint \(r=R\beta +e\), a new generalized difference-based weighted mixed almost unbiased ridge estimator is proposed. The performance of this estimator over the generalized difference-based weighted mixed estimator, the generalized difference-based estimator, and the generalized difference-based almost unbiased ridge estimator in terms of the mean square error matrix criterion is investigated. Then, a method to select the biasing parameter k and non-stochastic weight \(\omega \) is considered. The efficiency properties of the new estimator is illustrated by a simulation study. Finally, the performance of the new estimator is evaluated for a real dataset.


Difference-based estimator Generalized ridge estimator Generalized difference-based weighted mixed almost unbiased ridge estimator Partially linear model Weighted mixed estimator 

Mathematics Subject Classification

Primary 62 G05 Seconday 62J05 62J07 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of Mathematics and Computer ScienceÇağ UniversityTarsus-MersinTurkey
  2. 2.Faculty of Mathematics, Statistics and Computer ScienceSemnan UniversitySemnanIran

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