New robust-ridge estimators for partially linear model

Elgohary, M. M., M. R. Abonazel, N. M. Helmy, and A. R. Azazy, "New robust-ridge estimators for partially linear model", International Journal of Applied Mathematical Research, vol. 8, no. 2, pp. 46–52, 2019.


This paper considers the partially linear model when the explanatory variables are highly correlated as well as the dataset contains outliers. We propose new robust biased estimators for this model under these conditions. The proposed estimators combine least trimmed squares and ridge estimations, based on the spline partial residuals technique. The performance of the proposed estimators and the Speckman-spline estimator has been examined by a Monte Carlo simulation study. The results indicated that the proposed estimators are more efficient and reliable than the Speckman-spline estimator.