This paper considers the convergence rates for nonparametric estimators of the error distribution in semi-parametric regression models. By establishing some general laws of the iterated logarithm, it shows that the ra...This paper considers the convergence rates for nonparametric estimators of the error distribution in semi-parametric regression models. By establishing some general laws of the iterated logarithm, it shows that the rates of convergence of either the empirical distribution or a smoothed version of the empirical distribution function matches exactly the rates obtained for an independent sample from the error distribution.展开更多
基金supported by the National Science Foundation of China under Grant Nos.11201422,11301481,and 11371321Zhejiang Provincial Natural Science Foundation of China under Grant Nos.Y6110639,Y6110110,LQ12A01018,and LQ12A01017+2 种基金the National Statistical Science Research Project of China under Grant No.2012LY174Foundation for Young Talents of ZJGSU under Grant No.1020XJ1314019Zhejiang Provincial Key Research Base for Humanities and Social Science Research(Statistics)
文摘This paper considers the convergence rates for nonparametric estimators of the error distribution in semi-parametric regression models. By establishing some general laws of the iterated logarithm, it shows that the rates of convergence of either the empirical distribution or a smoothed version of the empirical distribution function matches exactly the rates obtained for an independent sample from the error distribution.
