[1] Thode Jr., H.C. (2012) Testing for Normality. Marcel Dekker, Inc., New York.
[2] Shapiro, S.S. and Wilk, M.B. (1965) An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52, 591-611.
http://dx.doi.org/10.1093/biomet/52.3-4.591
[3] Royston, T.P. (1982) An Extension of Shapiro and Wilk W Test for Normality to Large Samples. Applied Statistics, 31, 115-124.
http://dx.doi.org/10.2307/2347973
[4] Royston, T.P. (1983) Some Techniques for Assessing Multivarate Normality Based on the Shapiro-Wilk W. Applied Statistics, 32, 121-133.
http://dx.doi.org/10.2307/2347291
[5] Royston, T.P. (1992) Approximating the Shapiro-Wilk W-Test for Non-Normality. Statistics and Computing, 2, 117-119.
http://dx.doi.org/10.1007/BF01891203
[6] Royston, J.P. (1995) Remark AS R94: A Remark on Algorithm AS 181: The W Test for Normality. Applied Statistics, 44, 547-551.
http://dx.doi.org/10.2307/2986146
[7] Korkmaz, S. (2013) Royston’s H Test: Multivariate Normality Test.
http://cran.r-project.org/web/packages/royston/index.html
[8] Villase?or-Alva, J.A. and González-Estrada, G. (2009) A Generalization of Shapiro-Wilk’s Test for Multivariate Normality. Communications in Statistics-Theory and Methods, 38, 1870-1883.
http://dx.doi.org/10.1080/03610920802474465
[9] Gonzalez-Estrada, G. and Villase?or-Alva, J.A. (2013) Generalized Shapiro-Wilk Test for Multivariate Normality.
http://rpackages.ianhowson.com/cran/mvShapiroTest/
[10] Fattorini, L. (1986) Remarks on the Use of the Shapiro-Wilk Statistic for Testing Multivariate Normality. Statistica, 46, 209-217.
[11] Henze, N. and Zirkler, B. (1990) A Class of Invariant Consistent Tests for Multivariate Normality. Communications in Statistics-Theory and Method, 19, 3595-3618.
http://dx.doi.org/10.1080/03610929008830400
[12] Malkovich, J.F. and Afifi, A.A. (1973) On Tests for Multivariate Normality. Journal of American Statistical Association, 68, 713-718.
http://dx.doi.org/10.1080/01621459.1973.10481358
[13] Mudholkar, G., Srivastava, D. and Lin, C. (1995) Some p-Variate Adaptations of the Shapiro-Wilk Test of Normality. Communications in Statistics-Theory and Method, 24, 953-985.
http://dx.doi.org/10.1080/03610929508831533
[14] Srivastava, M. and Hui, T. (1987) On Assessing Multivariate Normality Based on Shapiro-Wilk W Statistic. Statistics and Probability Letters, 5, 15-18.
http://dx.doi.org/10.1016/0167-7152(87)90019-8
[15] Shao, Y. and Zhou, M. (2010) A Characterization of Multivariate Normality through Univariate Projections. Journal of Multivariate Analysis, 101, 2637-2640.
http://dx.doi.org/10.1016/j.jmva.2010.04.015
[16] Fisher, R.A. (1936) The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics, 7, 179-188.
http://dx.doi.org/10.1111/j.1469-1809.1936.tb02137.x
[17] Looney, S.W. (1995) How to Use Tests for Univariate Normality to Assess Multivariate Normality. The American Statistician, 49, 64-70.
[18] Small, N. (1980) Marginal Skewness and Kurtosis in Testing Multivariate Normality. Applied Statistics, 29, 85-87.
http://dx.doi.org/10.2307/2346414
[19] Mardia, K.V. (1974) Applications of Some Measures of Multivariate Skewness and Kurtosis in Testing Normality and Robustness Studies. Sankhyā: The Indian Journal of Statistics, Series B, 36, 115-128.
[20] Srivastava, M.S. (1984) A Measure of Skewness and Kurtosis and a Graphical Method for Assessing Multivariate Normality. Statistics and Probability Letters, 2, 263-267.
http://dx.doi.org/10.1016/0167-7152(84)90062-2
[21] Zhou, M. and Shao, Y. (2014) A Powerful Test for Multivariate Normality. Journal of Applied Statistics, 41, 351-363.
http://dx.doi.org/10.1080/02664763.2013.839637