Diagnostic limitations of skewness coefficients in assessing departures from univariate and multivariate normality
作者:
Ronaldl. Horswell,
Stephenw. Looney,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1993)
卷期:
Volume 22,
issue 2
页码: 437-459
ISSN:0361-0918
年代: 1993
DOI:10.1080/03610919308813102
出版商: Marcel Dekker, Inc.
关键词: kurtosis;multivariate;normality;radii;skewness;univariate normality
数据来源: Taylor
摘要:
While many tests of univariate and multivariate normality have been proposed, those based on skewness and kurtosis coefficients are widely presumed to offer the advantage of diagnosing how distributions depart from normality. However, results summarized from many Monte Carlo studies show that tests based on skewness coefficients do not reliably discriminate between skewed and non-skewed distributions. Indeed, the use of skewness tests to discriminate between these distributions lackstheoretical foundation. The performance of skewness tests is shown to be very sensitive to the kurtosis of the underlying distribution
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