Comparison of some methods for estimating a polynomial regression model using simulation
DOI:
https://doi.org/10.17762/msea.v71i4.549Abstract
In this research, estimators and parameters of the second-order polynomial regression model were found when the random error distribution was long-tailed symmetric using the Modified Maximum likelihood Method and the Robust M method. These methods proved their efficiency more than the ordinary least squares method through comparison between them using mean square error and simulation for three sample sizes (60, 90, 120).