論文

査読有り
2018年5月28日

A Monte Carlo comparison of Jarque–Bera type tests and Henze–Zirkler test of multivariate normality

Communications in Statistics: Simulation and Computation
  • Zofia Hanusz
  • ,
  • Rie Enomoto
  • ,
  • Takashi Seo
  • ,
  • Kazuyuki Koizumi

47
5
開始ページ
1439
終了ページ
1452
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1080/03610918.2017.1315771
出版者・発行元
Taylor and Francis Inc.

In the paper, tests for multivariate normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based on skewness and kurtosis defined by Jarque and Bera have been taken into account. In the Monte Carlo simulations, for each combination of p = 2, 3, 4, 5 number of traits and n = 10(5)50(10)100 sample sizes 10,000 runs have been done to calculate empirical Type I errors of tests under consideration, and empirical power against different alternative distributions. Simulation results have been compared to the Henze–Zirkler’s test. It should be stressed that no test yet proposed is uniformly better than all the others in every combination of conditions examined.

リンク情報
DOI
https://doi.org/10.1080/03610918.2017.1315771
ID情報
  • DOI : 10.1080/03610918.2017.1315771
  • ISSN : 1532-4141
  • ISSN : 0361-0918
  • SCOPUS ID : 85021426577

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