A test for multivariate normality based on sample entropy and projection pursuit

Li-Xing Zhu, Hoi Lam Wong, Kai-Tai Fang*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

30 Citations (Scopus)


Testing normality and multinormality has long been an interesting issue in statistical inferences. Many tests have been proposed. In particular, Vasicek (J. Roy. Statist. Soc. A 139 (1976), 54-59) suggested a test based on sample entropy. A similar idea was extended to the multivariate case with projection pursuit for searching for departure from the multivariate normal distribution. We, in this paper, suggest a new test for multinormality based on density estimation, a number-theoretic method, projection pursuit technique and sample entropy. Our results show that the new test may be recommended for practice.

Original languageEnglish
Pages (from-to)373-385
Number of pages13
JournalJournal of Statistical Planning and Inference
Issue number3
Publication statusPublished - Jun 1995

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

User-Defined Keywords

  • 62G10
  • 62H40
  • 65C05
  • Density estimation
  • Entropy
  • Kurtosis
  • Multivariate normality
  • Number-theoretic method
  • Projection pursuit
  • Skewness


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