A comparison Between Two Methods Of Estimating a Semi-parametric Regression Model in The Presence of The Autocorrelation Problem
Keywords:
Semiparametric partial linear regression model, Semiparametric generalized least squares estimators, least squares estimators, Autocorrelation problemAbstract
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).
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