ESTIMATION IN MULTIFACTOR POLYNOMIAL REGRESSION UNDER NON-NORMALITY

Modified maximum likelihood estimators of the parameters in a second order polynomial regression model are derived. They are shown to be considerably more efiicient and robust than the commonly used least squares estimators. Real life examples are given