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 in partially linear model when the errors are correlated. A generalized-difference-based almost unbiased two-parameter estimator is defined for the vector parameter . Under the linear stochastic constraint r = R + 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.