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http://dx.doi.org/10.5351/CKSS.2012.19.4.607

A Goodness-of-Fit Test for Multivariate Normal Distribution Using Modified Squared Distance  

Yim, Mi-Hong (Department of Information Statistics, Chungnam National University)
Park, Hyun-Jung (Trends Analysis Division, Statistical Research Institute)
Kim, Joo-Han (Department of Information Statistics, Chungnam National University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.4, 2012 , pp. 607-617 More about this Journal
Abstract
The goodness-of-fit test for multivariate normal distribution is important because most multivariate statistical methods are based on the assumption of multivariate normality. We propose goodness-of-fit test statistics for multivariate normality based on the modified squared distance. The empirical percentage points of the null distribution of the proposed statistics are presented via numerical simulations. We compare performance of several test statistics through a Monte Carlo simulation.
Keywords
Multivariate normal distribution; goodness-of-fit test; empirical distribution function; modified squared distance;
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