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
β¦ LIBER β¦
Limit theorems for boundary function estimators
β 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
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β¦ Synopsis
Park et al. (Econometric Theory 16 (2000)
- 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.
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