Marginal Distributions of Random Vectors Generated by Affine Transformations of Independent Two-Piece Normal Variables
AbstractMarginal 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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Bibliographic InfoPaper provided by Banco de Portugal, Economics and Research Department in its series Working Papers with number w201013.
Date of creation: 2010
Date of revision:
Find related papers by JEL classification:
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
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- 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).
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- Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, EconWPA.
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