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A Semi-Parametric Quantile Function Estimator for Use in Bootstrap Estimation Procedures
Authors:Hutson  Alan D
Institution:(1) Geological and Environmental Sciences, Stanford University, Stanford, California, 94305-2220;(2) Department of Mathematics, Katholieke Universiteit Leuven, Celestijnenlaan 200B, 3001 Heverlee, Belgium;(3) Department of Civil Engineering, The University of Calgary, 2500 University Drive N.W., Calgary, AB, T2N 1N4, Canada
Abstract:In this note we develop a new quantile function estimator called the tail extrapolation quantile function estimator. The estimator behaves asymptotically exactly the same as the standard linear interpolation estimator. For finite samples there is small correction towards estimating the extreme quantiles. We illustrate that by employing this new estimator we can greatly improve the coverage probabilities of the standard bootstrap percentile confidence intervals. The method does not reqiure complicated calculations and hence it should appeal to the statistical practitioner.
Keywords:order statistics  quantile function  resampling
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