Moments of the complex multivariate normal distribution

Screening for a Multivariate Mixture Normal Distribution

R Functions to Symbolically Compute the Central and Non-central Moments of the Multivariate Normal Distribution

The central moments of the multivariate normal distribution are functions of its n×n variance-covariance matrix Σ. These moments can be expressed symbolically as linear combinations of products of powers of the elements of Σ. A formula for these moments derived by differentiating the characteristic function is developed. The formula requires searching integer matrices for matrices whose n succe...

R Functions to Symbolically Compute the Central Moments of the Multivariate Normal Distribution

The central moments of the multivariate normal distribution are functions of its n×n variance-covariance matrix Σ. These moments can be expressed symbolically as linear combinations of products of powers of the elements of Σ. A formula for these moments derived by differentiating the characteristic function is developed. The formula requires searching integer matrices for matrices whose n succe...

Moments and Absolute Moments of the Normal Distribution

We present formulas for the (raw and central) moments and absolute moments of the normal distribution. We note that these results are not new, yet many textbooks miss out on at least some of them. Hence, we believe that it is worthwhile to collect these formulas and their derivations in these notes.

The Complex Multivariate Gaussian Distribution

Here I introduce package cmvnorm, a complex generalization of the mvtnorm package. A complex generalization of the Gaussian process is suggested and numerical results presented using the package. An application in the context of approximating the Weierstrass σ-function using a complex Gaussian process is given.