𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Limit theorems for boundary function estimators

✍ Scribed by J.H. Hwang; B.U. Park; W. Ryu


Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
121 KB
Volume
59
Category
Article
ISSN
0167-7152

No coin nor oath required. For personal study only.

✦ Synopsis


Park et al. (Econometric Theory 16 (2000)

  1. and Gijbels et al. (J. Amer. Statist. Assoc. 94 (1999) 220) derived the limit distributions of the two most popular nonparametric estimators, FDH and DEA, of a boundary in a setting where the density or intensity of the data has a sharp or fault-type boundary. In this paper, we extend their results to the general case where the density or intensity may decrease to zero or inΓΏnity at a speed of power -1 ( ΒΏ 0) of the distance from the boundary.

πŸ“œ SIMILAR VOLUMES


Limit theorems for nonparametric sample
✍ Kai-Sheng Song πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 110 KB

We obtain, for the ΓΏrst time in the literature, the central limit theorem for nonparametric sample entropy estimators in its full generality together with maximum likelihood entropy estimators. Also we provide a new proof of the consistency of the estimators to correct some problems in Vasicek's ori

Central limit theorems for quadratic err
✍ Tae Yoon Kim πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 390 KB

Hall [J. Multivariate Anal. 14 (1984) 1-16; Ann. Statist. 12 (1984) 241 260] established central limit theorems for the integrated square errors of multivariate nonparametric function estimators. In this article, we extend his results and derive central limit theorems for the averaged square errors