Marginal Distributions of Random Vectors Generated by Affine Transformations of Independent Two-Piece Normal Variables
Marginal probability density and cumulative distribution functions are presented for multidimensional variables defined by non-singular affine transformations of vectors of independent two-piece normal variables, the most important subclass of Ferreira and Steel’s general multivariate skewed distributions. The marginal functions are obtained by first expressing the joint density as a mixture of Arellano-Valle and Azzalini’s unified skew-normal densities and then using the property of closure under marginalization of the latter class.
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- Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007.
"Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers,"
Journal of Econometrics,
Elsevier, vol. 137(2), pages 641-673, April.
- Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Model Comparison of Coordinate-Free Multivariate Skewed Distributions with an Application to Stochastic Frontiers," Econometrics 0404005, EconWPA.
- Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).
- Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, EconWPA. Full references (including those not matched with items on IDEAS)
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