Showing papers on "Coverage probability published in 1983"
TL;DR: In this article, a confidence set for the mean of a multivariate normal distribution is derived through the use of an empirical Bayes argument, which is easy to compute and has uniformly smaller volume than the usual confidence set.
Abstract: Through the use of an empirical Bayes argument, a confidence set for the mean of a multivariate normal distribution is derived. The set is a recentered sphere, is easy to compute, and has uniformly smaller volume than the usual confidence set. An exact formula for the coverage probability is derived, and numerical evidence is presented which shows that the empirical Bayes set uniformly dominates the usual set in coverage probability.
63 citations
TL;DR: The coverage probability and ASN of the Stein's two-stage confidence interval procedure for estimating the normal mean have been obtained under the assumption that the underlying distribution is, in fact, different from normal but could be approximated by the first four terms of Edgeworth series.
Abstract: The expressions for coverage probability and ASN of the Stein's two-stage confidence interval procedure for estimating the normal mean have been obtained under the assumption that the underlying distribution is, in fact, different from normal but could be approximated by the first four terms of Edgeworth series. The comparison of coverage probabilities with the corresponding probabilities obtained for the normal distribution shows that the procedure is quite insensitive to moderate departures from normality, and skewness of the parent population has very little effect on the coverage probability of the procedure. The Monte Carlo investigations which involve sampling from the gamma population confirm these conclusions.
11 citations