On Dominating an Average Associated with Dependent Gaussian Vectors

Autoregressive Gaussian Random Vectors of First Order

A note on dominating sets and average distance

We show that the total domination number of a simple connected graph is greater than the average distance of the graph minus one-half, and that this inequality is best possible. In addition, we show that the domination number of the graph is greater than two-thirds of the average distance minus one-third, and that this inequality is best possible. Although the latter inequality is a corollary t...

Balancing Gaussian Vectors

Let x1, . . . xn be independent normally distributed vectors on Rd. We determine the distribution function of the minimum norm of the 2n vectors ±x1 ± x2 · · · ± xn.

Gaussian Random Vectors

1. The multivariate normal distribution Let X := (X1 � � � � �X�) be a random vector. We say that X is a Gaussian random vector if we can write X = μ + AZ� where μ ∈ R, A is an � × � matrix and Z := (Z1 � � � � �Z�) is a �-vector of i.i.d. standard normal random variables. Proposition 1. Let X be a Gaussian random vector, as above. Then, EX = μ� Var(X) := Σ = AA� and MX(�) = e � μ+ 1 2 �A���2 =...

autoregressive gaussian random vectors of first order