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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/15131

Title: Multivariate extension of chi-squared univariate normality test
???metadata.dc.creator???: Oliveira, I. R. Cardoso de
Ferreira, D. F.
Keywords: Chi-squared
Normality test
Multivariate extension
Monte Carlo simulation
Teste de normalidade
Extensão multivariada
Simulação de Monte Carlo
Publisher: Taylor & Francis Group
Issue Date: 2010
Citation: OLIVEIRA, I. R. C. de; FERREIRA, D. F. Multivariate extension of chi-squared univariate normality test. Journal of Statistical Computation and Simulation, New York, v. 80, n. 5, p. 513-526, 2010.
Abstract: We propose a multivariate extension of the univariate chi-squared normality test. Using a known result for the distribution of quadratic forms in normal variables, we show that the proposed test statistic has an approximated chi-squared distribution under the null hypothesis of multivariate normality. As in the univariate case, the new test statistic is based on a comparison of observed and expected frequencies for specified events in sample space. In the univariate case, these events are the standard class intervals, but in the multivariate extension we propose these become hyper-ellipsoidal annuli in multivariate sample space. We assess the performance of the new test using Monte Carlo simulation. Keeping the type I error rate fixed, we show that the new test has power that compares favourably with other standard normality tests, though no uniformly most powerful test has been found. We recommend the new test due to its competitive advantages.
URI: http://www.tandfonline.com/doi/abs/10.1080/00949650902731377
http://repositorio.ufla.br/jspui/handle/1/15131
???metadata.dc.language???: en_US
Appears in Collections:DEX - Artigos publicados em periódicos

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