Open Access
Translator Disclaimer
September, 1983 A Normal Limit Law for a Nonparametric Estimator of the Coverage of a Random Sample
Warren W. Esty
Ann. Statist. 11(3): 905-912 (September, 1983). DOI: 10.1214/aos/1176346256

Abstract

The coverage of a multinomial random sample is the sum of the probabilities of the observed classes. A normal limit law is rigorously proved for Good's (1953) coverage estimator. The result is valid under very general conditions and all terms except the coverage itself are observable. Nevertheless the implied confidence intervals are not much wider than those developed under restrictive assumptions such as in the classical occupancy problem. The asymptotic variance is somewhat unexpected. The proof utilizes a method of Holst (1979).

Citation

Download Citation

Warren W. Esty. "A Normal Limit Law for a Nonparametric Estimator of the Coverage of a Random Sample." Ann. Statist. 11 (3) 905 - 912, September, 1983. https://doi.org/10.1214/aos/1176346256

Information

Published: September, 1983
First available in Project Euclid: 12 April 2007

zbMATH: 0599.62053
MathSciNet: MR707940
Digital Object Identifier: 10.1214/aos/1176346256

Subjects:
Primary: 62G15
Secondary: 60F05, 62E20

Rights: Copyright © 1983 Institute of Mathematical Statistics

JOURNAL ARTICLE
8 PAGES


SHARE
Vol.11 • No. 3 • September, 1983
Back to Top