ASYMPTOTIC PROPERTIES OF NONPARAMETRIC FRONTIER ESTIMATORS
研究了非参数前沿估计中经验条件分位数函数的弱收敛性，并给出无需估计条件分位数密度即可构造均匀置信带的方法。
Aragon, Daouia, and Thomas-Agnan (2005, Econometric Theory 21, 358–389) introduced a new nonparametric frontier estimation. We prove the weak convergence of the empirical conditional quantile function. The distribution of the limit depends on the unknown conditional quantile density function. We provide a method to construct uniform confidence bands without estimating the conditional quantile density.