Expectations of useful complex Wishart forms
Multidimensional Systems and Signal Processing
MacMahon's Master Theorem, Representation Theory, and Moments of Wishart Distributions
Advances in Applied Mathematics
A trivariate chi-squared distribution derived from the complex Wishart distribution
Journal of Multivariate Analysis
Distribution and characteristic functions for correlated complex Wishart matrices
Journal of Multivariate Analysis
Polarimetric synthetic aperture radar data and the complex wishart distribution
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Largest eigenvalue of complex Wishart matrices and performance analysis of MIMO MRC systems
IEEE Journal on Selected Areas in Communications
On a symbolic representation of non-central Wishart random matrices with applications
Journal of Multivariate Analysis
Hi-index | 0.00 |
We summarize the main results known for the complex normal and complex Wishart, then give the cumulants of the central and noncentral complex Wishart. Their moments are expressed explicitly in terms of multivariate Bell polynomials, believed to be used here for the first time. Multivariate Bell polynomials are easily written down from their univariate forms, which are widely accessible in most computer algebra packages. This is shown to be the natural way of obtaining the moments for any sum of independent and identically distributed (i.i.d.) random variables. An extension is given to the weighted complex Wishart.