NONPARAMETRIC ESTIMATION FOR A GENERAL, REGRESSION MODEL
ZHENG ZHONGGUO (Peking University, Beijing)
In this paper, the estimation of the direction of the regression ooeffcient of the general regression model is considered. Li and Duan use maximum likelihood type criteria to get a consistent series of estimators of the direction. The condition, which they imposed on the distribution of the regressor variable X in their construction of the estimators, is very restrictive. In this paper, to avoid the restrictive condition, a nonparametric estimator of the direction of the general regression model is constructed. The estimator is proved to be consistent.