Estimation of a star-shaped distribution function

被引：0
|
作者：
El Barmi, Hammou [1 ]
Malla, Ganesh [2 ]
Mukerjee, Hari [3 ]
机构：
[1] CUNY, Baruch Coll, Stat & CIS, One Baruch Way,Box 11-220, New York, NY 10010 USA
[2] Univ Cincinnati, Math Comp Geol & Phys, Clermont Coll, Batavia, OH 45103 USA
[3] Wichita State Univ, Math & Stat, Wichita, KS 67260 USA
来源：
JOURNAL OF NONPARAMETRIC STATISTICS | 2017年 / 29卷 / 01期
关键词：
Star-shaped distribution functions; uniform consistency; convergence in distribution; argmax theorem;
D O I：
10.1080/10485252.2016.1239827
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：
A life distribution function (DF) F is said to be star-shaped if F(x)/x is nondecreasing on its support. This generalises the model of a convex DF, even allowing for jumps. The nonparametric maximum likelihood estimation is known to be inconsistent. We provide a uniformly strongly consistent least-squares estimator. We also derive the convergence in distribution of the estimator at a point where F(x)/x is increasing using the arg max theorem.
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页码：22 / 39
页数：18
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