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1	Moments and Quadratic Forms of Matrix Variate Skew Normal Distributions Zheng, Shimin, Knisley, Jeff, Wang, Kesheng 01 February 2016 (has links) In 2007, Domínguez-Molina et al. obtained the moment generating function (mgf) of the matrix variate closed skew normal distribution. In this paper, we use their mgf to obtain the first two moments and some additional properties of quadratic forms for the matrix variate skew normal distributions. The quadratic forms are particularly interesting because they are essentially correlation tests that introduce a new type of orthogonality condition. correlation matrix variate moment moment generating function primary 62H10 quadratic form secondary 62H05 skew normal distribution Biostatistics and Epidemiology Biostatistics Mathematics
2	The Inverse Problem of Multivariate and Matrix-Variate Skew Normal Distributions Zheng, Shimin, Hardin, J. M., Gupta, A. K. 01 June 2012 (has links) In this paper, we prove that the joint distribution of random vectors Z 1 and Z 2 and the distribution of Z 2 are skew normal provided that Z 1 is skew normally distributed and Z 2 conditioning on Z 1 is distributed as closed skew normal. Also, we extend the main results to the matrix variate case. closed skew normal distribution conditional distribution matrix variate skew normal distribution multivariate distribution normal distribution Primary: 62H10 Secondary: 62H05 skew normal distribution Biostatistics and Epidemiology Biostatistics Mathematics

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Moments and Quadratic Forms of Matrix Variate Skew Normal Distributions

The Inverse Problem of Multivariate and Matrix-Variate Skew Normal Distributions