A power study of goodness-of-fit tests for multivariate normality implemented in R

DOI10.1080/00949655.2012.739620zbMath1453.62522OpenAlexW1997545438MaRDI QIDQ5219964

Jürgen Vogel, Dieter W. Joenssen

Publication date: 9 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.739620

zbMATH Keywords

hypothesis testingmultivariate normalitygoodness-of-fit testtype I errorpower comparison

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Software, source code, etc. for problems pertaining to statistics (62-04) Hypothesis testing in multivariate analysis (62H15)

Related Items (8)

On energy tests of normality ⋮ Likelihood ratio tests for multivariate normality ⋮ A new large sample goodness of fit test for multivariate normality based on chi squared probability plots ⋮ Are You All Normal? It Depends! ⋮ A new class of tests for multinormality with i.i.d. And garch data based on the empirical moment generating function ⋮ Testing for normality in any dimension based on a partial differential equation involving the moment generating function ⋮ Tests for multivariate normality -- a critical review with emphasis on weighted $L^2$-statistics ⋮ A MATLAB package for multivariate normality test

Uses Software

• R
• mvtnorm
• nortest
• MersenneTwister
• energy
• ICS
• mvShapiroTest
• AS 181
• AS 183
• mvnormtest
• QRMlib
• QuantPsyc
• AS 177
• normwn.test
• mvsf

Cites Work

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• A Generalization of Shapiro–Wilk's Test for Multivariate Normality
• Tests of multinormality based on location vectors and scatter matrices
• A comparative study of goodness-of-fit tests for multivariate normality
• A new test for multivariate normality
• Computation of multivariate normal and \(t\) probabilities
• Data driven smooth tests for bivariate normality
• An Extension of Shapiro and Wilk's W Test for Normality to Large Samples
• A Bivariate Model for the Distribution of √b 1 and b 2
• Mersenne twister
• On Mardia’s kurtosis test for multivariate normality
• An analysis of variance test for normality (complete samples)
• On tests for multivariate normality and associated simulation studies
• A Monte Carlo comparison of the Type I and Type II error rates of tests of multivariate normality
• Measures of multivariate skewness and kurtosis with applications
• A SIMPLE TEST OF NORMALITY FOR TIME SERIES

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