Matrix variate Kummer-Dirichlet distributions.
Matrix-variate beta distribution.
Minimum Variance Unbiased Estimation of Multivariate Modified Power Series Distribution.
Mixturas de distribuciones normales con aplicaciones a problemas estadísticos complejos.
Multivariate Gamma Distributions with One-Factorial Accompanying Correlation Matrices and Applications to the Distribution of the Multivariate Range.
Multivariate multiple comparisons with a control in elliptical populations
The approximate upper percentile of Hotelling's T²-type statistic is derived in order to construct simultaneous confidence intervals for comparisons with a control under elliptical populations with unequal sample sizes. Accuracy and conservativeness of Bonferroni approximations are evaluated via a Monte Carlo simulation study. Finally, we explain the real data analysis using procedures derived in this paper.
Multivariate skewness and kurtosis for singular distributions.
In multivariate analysis it is generally assumed that the observations are normally distributed. It was Mardia ([1] to [5]), who first introduced measures of multivariate skewness and kurtosis; these statistics are affine invariant and can be used for testing multivariate normality. Skewness and kurtosis tests remain among the most powerful, general and easy to implement. In this paper we show some properties of these statistics when population distribution is singular.