Elliptically contoured models in statistics
Elliptically contoured models in statistics
Distribution of sum of squares and products matrices for the generalized multilinear matrix-T model
Journal of Multivariate Analysis
The Matsumoto--Yor property and the structure of the Wishart distribution
Journal of Multivariate Analysis
Properties of the singular, inverse and generalized inverse partitioned Wishart distributions
Journal of Multivariate Analysis
| Hi-index | 0.00 |
In this paper we consider the distribution of the product of a Wishart random matrix and a Gaussian random vector. We derive a stochastic representation for the elements of the product. Using this result, the exact joint density for an arbitrary linear combination of the elements of the product is obtained. Furthermore, the derived stochastic representation allows us to simulate samples of arbitrary size by generating independently distributed chi-squared random variables and standard multivariate normal random vectors for each element of the sample. Additionally to the Monte Carlo approach, we suggest another approximation of the density function, which is based on the Gaussian integral and the third order Taylor expansion. We investigate, with a numerical study, the properties of the suggested approximations. A good performance is documented for both methods.