Unified estimators of smooth quantile and quantile density functions

被引:44
作者
Cheng, C
Parzen, E
机构
[1] JOHNS HOPKINS UNIV, DEPT MATH SCI, BALTIMORE, MD 21218 USA
[2] TEXAS A&M UNIV, DEPT STAT, COLLEGE STN, TX 77843 USA
关键词
quantile; quantile density; kernel; smoothing; Bernstein polynomial; efficiency; monotone; convex;
D O I
10.1016/S0378-3758(96)00110-3
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Diverse smooth estimators of quantile functions are unified into generalized kernel smoothers of the sample quantile function. Sup-norm convergence of the quantile function estimators and the derived quantile density function estimators are established. The convergence rates reveal the simultaneous uniform in-probability consistency of both estimators on any compact set inside the open unit interval. A Berry-Esseen-type theorem of the quantile function estimators is established; the asymptotic deficiency of sample quantiles relative to the smooth estimators and optimal smoothing rate are determined. Oscillation behavior of the estimators in finite samples (monotonicity, convexity, etc.) is investigated, and is related to certain algebraic properties of the smoothing kernel.
引用
收藏
页码:291 / 307
页数:17
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