Detecting Heteroscedasticity in Non-Parametric Regression Using Weighted Empirical Processes
利用加权经验过程检验非参数回归中的异方差
Summary Heteroscedastic errors can lead to inaccurate statistical conclusions if they are not properly handled. We introduce a test for heteroscedasticity for the non-parametric regression model with multiple covariates. It is based on a suitable residual-based empirical distribution function. The residuals are constructed by using local polynomial smoothing. Our test statistic involves a ‘detection function’ that can verify heteroscedasticity by exploiting just the…