• THE PERFORMANCE OF SPECKMAN ESTIMATION FOR PARTIALLY LINEAR MODEL USING KERNEL AND SPLINE SMOOTHING APPROACHES

MOHAMED R. ABONAZEL*, NAHED HELMY, ABEER R. AZAZY

Abstract


The Speckman method is a commonly used for estimating the partially linear model (PLM). This method used the kernel approach to estimate nonparametric part in PLM. In this paper, we suggest using the spline approach instead of the kernel approach. Then we present a comparative study of the two estimations based on two smoothing (kernel and spline) approaches. A simulation study has been conducted to evaluate the performance of these estimations. The results of our study confirmed that the spline smoothing approach was the best.


Keywords


Kernel smoothing; Mote Carlo simulation, Nonparametric regression; Spline smoothing; Semi-parametric regression.

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