T-Convolution and its applications to \(n\)-dimensional distributions

In this paper we introduce the notion of T-convolution, which is a generalization of
convolution to higher dimensions. By using T-convolution we construct n-dimensional distributions
having n+1 axes of symmetry. In addition, we can generalize well-known symmetric
probability distributions in one dimension to higher dimensions. In particular, we consider
generalizations of Laplace and triangle continuous distributions and we show their plots in the
two-dimensional case. As an example of discrete distributions, we study the T-convolution of
Poisson distributions in the plane.