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Title: A second order approximation for the inverse of the distribution function of the sample mean (English)
Author: Arevalillo, Jorge M.
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 37
Issue: 1
Year: 2001
Pages: [91]-102
Summary lang: English
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Category: math
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Summary: The classical quantile approximation for the sample mean, based on the central limit theorem, has been proved to fail when the sample size is small and we approach the tail of the distribution. In this paper we will develop a second order approximation formula for the quantile which improves the classical one under heavy tails underlying distributions, and performs very accurately in the upper tail of the distribution even for relatively small samples. (English)
Keyword: tail probabilities
Keyword: saddlepoint approximations
MSC: 60F05
MSC: 62E15
MSC: 62E17
MSC: 62G20
MSC: 62G32
idZBL: Zbl 1264.62044
idMR: MR1825759
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Date available: 2009-09-24T19:37:25Z
Last updated: 2015-03-26
Stable URL: http://hdl.handle.net/10338.dmlcz/135391
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Reference: [3] Daniels H. E.: Saddlepoint approximations in statistics.Ann. Math. Statist. 25 (1954), 631–649 Zbl 0058.35404, MR 0066602, 10.1214/aoms/1177728652
Reference: [4] Feller W.: An Introduction to Probability Theory and its Applications.Vol. I. Wiley, New York 1968 Zbl 0598.60003, MR 0228020
Reference: [5] Field C. A., Ronchetti E.: A tail area influence function and its application to testing.Comm. Statist. C 4 (1985), 19–41 Zbl 0592.62030, MR 0795262
Reference: [6] García–Pérez A.: Behaviour of sign test and one sample median test against changes in the model.Kybernetika 32 (1996), 159–173 Zbl 0873.62046, MR 1385860
Reference: [7] Jensen J. L.: Saddlepoint Approximations.Oxford University Press, New York 1995 Zbl 0764.62021, MR 1354837
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