Using the bootstrap in testing symmetry versus asymmetry
作者:
Schuster Eugene F,
Richard C Barker,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1987)
卷期:
Volume 16,
issue 1
页码: 69-84
ISSN:0361-0918
年代: 1987
DOI:10.1080/03610918708812578
出版商: Marcel Dekker, Inc.
关键词: empirical cdf;nonparametric test;testing symmetry;center of symmetry;symmetric bootstrap;estimating;p-values
数据来源: Taylor
摘要:
One approach to testing the hypothesis of symmetry versus asymmetry is to use estimates of the center of symmetry in nonparametric tests about a known center. The problem with this approach is that the resulting tests are not distribution-free. Hence, one cannot compute critical values, p-values, or probabilities of errors for these tests. We propose to sidestep this problem with a symmetric bootstrap procedure which uses bootstrap samples from (a smoothed version of) the closest symmetric distribution to the empirical distribution of the data to estimate these values. In this paper, we report simulation experience with this approach in testing the hypothesis of symmetry using the Schuster and Narvarte estimator of the center of symmetry in the so-called Butler sup norm test for symmetry about a known center.
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