Journal of Statistics: Advances in Theory and ApplicationsAuthor's: Kazuyuki Koizumi, Naoya Okamoto and Takashi Seo
Pages: [207] - [220]
Received Date: June 31, 2009
Submitted by:
In this paper, we consider some tests for the multivariate normality based on the sample measures of multivariate skewness and kurtosis. Sample measures of multivariate skewness and kurtosis were defined by Mardia [3], Srivastava [9] and so on. We derive new multivariate normality tests by using Mardia’s and Srivastava’s moments. For univariate case, Jarque and Bera [1] proposed bivariate test using skewness and kurtosis. We propose some new bivariate tests for assessing multivariate normality which are natural extensions of Jarque-Bera test. Finally, the numerical results by Monte Carlo simulation are shown in order to evaluate accuracy of expectations, variances and upper percentage points for new test statistics proposed in this paper.
Jarque-Bera test, multivariate skewness, multivariate kurtosis, normality test.
