A comparison Between Two Methods Of Estimating a Semi-parametric Regression Model in The Presence of The Autocorrelation Problem

Abstract

In this research, a comparison was made between two methods for estimating a semiparametric regression model with the presence of an autocorrelation problem, based on a semiparametric partial linear regression model, which contains a parametric component and a nonparametric component. The two components were estimated using two methods, the first methods is semi parametric generalized least squares estimators(SGLSE) , the second methods is least squares estimators method(LSEM) .Simulation study show the first method is beast than the second method by using mean squares of errors (MSE).

Keywords

• semiparametric partial linear regression model
• semiparametric generalized least squares estimators
• least squares estimators
• autocorrelation problem