Moderate deviations for a nonparametric estimator of sample coverage

Abstract

In this paper, we consider moderate deviations for Good's coverage estimator. The moderate deviation principle and the self-normalized moderate deviation principle for Good's coverage estimator are established. The results are also applied to the hypothesis testing problem and the confidence interval for the coverage.

Published in at http://dx.doi.org/10.1214/13-AOS1091 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (4)

• Delta method in large deviations and moderate deviations for estimators
• Estimation of sums of random variables: Examples and information bounds
• Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown
• Asymptotic normality of a nonparametric estimator of sample coverage