Assessing normality of high-dimensional data

Communications in Statistics: Simulation and Computation

Volumn 42, Issue 2, 2013, Pages 360-369

  Holgersson, H E T ^a   Mansoor, Rashid ^a  

^a JÖNKÖPING INTERNATIONAL BUSINESS SCHOOL   (Sweden)

Author keywords

Asymptotics; Increasing dimension; Multivariate skewness and kurtosis; Non normality

Indexed keywords

ASYMPTOTICS; HIGH DIMENSIONAL DATA; INCREASING DIMENSION; INFERENCE METHODS; MONTE CARLO SIMULATION; MULTIVARIATE SKEWNESS AND KURTOSIS; NON-NORMALITY; SAMPLE SIZES;

CIRCUIT SIMULATION; SOFTWARE ENGINEERING; STATISTICS;

MONTE CARLO METHODS;

EID: 84870900232     PISSN: 03610918     EISSN: 15324141     Source Type: Journal    
DOI: 10.1080/03610918.2011.636164     Document Type: Article

References (19)

1. Csörgö, S., Heathcote, C. R. (1987). Testing for Symmetry, Biometrika 74(1):177-184.
2. Doornik, J. A., Hansen, H. (2008). An Omnibus Test for Univariate and Multivariate Normality, Oxford Bulletin of Economics and Statistics 70(s1):927-939.
3. Dufour, J. M., Farhat, A., Gardiol, L. and Khalaf, L. (1998). Simulation based Finite Sample Normality Test in Linear Regression, Econometric Journal 1:154-173.
4. Fasano, G., Franceschini, A. (1987). A multidimensional version of the Kolmogorov-Smirnov test, Monthly Notices of the Royal Astronomical Society 225:155-170.
5. Feuerverger, A., Mureika, R. A. (1977). The Empirical Characteristic Function and its Applications, The Annals of Statistics 5(1):89-97.
6. Girko, V. L. (1995). Statistical Analysis of Observations of Increasing Dimension, Dordrecht, Germany: Kluwer Academic Publishers.
7. Hair, J. F. Jr., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate Data Analysis, New Jersey: Pearson.
8. Heathcote, C. R., Rachev, S. T., Cheng, B. (1995). Testing Multivariate Symmetry, Journal of Multivariate Analysis 54:91-112.
9. Holgersson, H. E. T., Shukur, G. (2001). Some Aspects of Non Normality Tests in Systems of Regression Equations, Communications in Statistics - Computation and Simulation 30(2):291-310.
10. Holgersson, H. E. T. (2006). A Graphical Technique for Assessing Multivariate Non normality, Computational Statistics 21(1):141-150.
11. Hopkins, J. W., Clay, P. P. F. (1963). Some Empirical Distributions of Bivariate T2 and Homoscedasticity Criterion M Under Unequal Variance and Leptokurtosis, JASA 58(304):1048-1153.
12. Jarque, C. M., Mckenzie, C. R. (1995). Testing for Multivariate Normality in Simultaneous-Equation Models, Mathematics and Computers in Simulation 39(3-4):323-328.
13. Kolmogorov, A. N. (1933). Sulla Determinazione Empirica di une Legge di Distribuzione, Giornale Dell'Istituto Italiano Degli Attuari 4:83-91.
14. Koizumi, K. et al. (2009). On the Jarque-Bera tests for Multivariate Normality, Journal of Statistics: Advances in Theory and Applications 1:207-220.
15. Lukacs, E. A. (1942). Characterization of the Normal Distribution, Annals of Mathematical Statistics 13:91-93.
16. Lütkepohl, H., Theilen, B. (1991). Measures of Multivariate Skewness and Kurtosis for Tests of Nonnormality, Statistical Papers 32:179-193.
17. Mardia, K.V. (1970). Measures of Multivariate Skewness and Kurtosis with Applications, Biometrika 57(3):519-530.
18. Serdobolskii, V. I. (2008). Multiparametric Statistics, Oxford: Elsevier.
19. Srivastava, M. S. (1984). A Measure of the Skewness and Kurtosis and a Graphical Method for Assessing Multivariate Normality, Statistics and Probability Letters 5:15-18.