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Research Report SRR02-005

Higher order comparisons of nonparametric confidence intervals

Yoshihiko Maesono

Abstract: In this paper we discuss properties of nonparametric confidence intervals based on asymptotic expansions. We consider the intervals which are based on a normalizing transformation and a Cornish-Fisher inversion of studentized statistics. The normalizing transformation that we discuss here removes bias, skewness and kurtosis, simultaneously. The Cornish-Fisher inversion is obtained from the Edgeworth expansion of the studentized statistic with residual term o(n-1). Asymptotic mean squared errors and simulation results are discussed.

Primary AMS Classification: 62G20
Date: 17 June 2002

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