Efficiency of the generalized-difference-based weighted mixed almost unbiased two-parameter estimator in partially linear model

ABSTRACT

In this paper, a generalized difference-based estimator is introduced for the vector parameter β in partially linear model when the errors are correlated. A generalized-difference-based almost unbiased two-parameter estimator is defined for the vector parameter β. Under the linear stochastic constraint r = Rβ + e, we introduce a new generalized-difference-based weighted mixed almost unbiased two-parameter estimator. The performance of this new estimator over the generalized-difference-based estimator and generalized- difference-based almost unbiased two-parameter estimator in terms of the MSEM criterion is investigated. 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.

KEYWORDS:

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

MATHEMATICS SUBJECT CLASSIFICATION:

• Primary 62G08
• Secondary 62J07

Acknowledgments

The authors are grateful to the anonymous reviewers and the associate editor for their valuable comments which helped to improve the quality of this work. The second author's research was supported in part by Research Councils of Semnan University, Iran.