Local Polynomial Regression for Heteroscedaticity in the Simple Linear Model
Qi Fang He · Systems Engineering-Theory Methodology Application · 2003
We introduce the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to heteroscedastic linear regression model. One noteworthy feature of our approach is avoiding the testing for heteroscedasticity. We establish the uniform consistency and derive the asymptotic distribution. Simulation results show that our approach is effective in finite sample situations as well.