Rodriguez, A.,Tsallis, C.
We introduce a family of dimension scale-invariant Leibniz-like pyramids and (d + 1)-dimensional hyperpyramids (d = 1, 2, 3, ... ), with d = 1 corresponding to triangles, d = 2 to (tetrahedral) pyramids, and so on. For all values of d, they are characterized by a parameter nu > 0, whose value determines the degree of correlation between N (d + 1)-valued random variables (d = 1 corresponds to binary variables, d = 2 to ternary variables, and so on). There are (d + 1)(N) different events, and the limit nu -> infinity corresponds to independent random variables, in which case each event has a probability 1/(d + 1)(N) to occur. The sums of these N (d + 1)-valued random variables correspond to a d-dimensional probabilistic model and generalize a recently proposed one-dimensional (d = 1) model having q - Gaussians (with q = (nu - 2)/(nu - 1) for nu epsilon [1,infinity)) as N -> infinity limit probability distributions for the sum of the N binary variables [A. Rodriguez, V! . Schwammle, and C. Tsallis, J. Stat. Mech.: Theory Exp. 2008, P09006; R. Hanel, S. Thurner, and C. Tsallis, Eur. Phys. J. B 72, 263 (2009)]. In the nu -> infinity limit the d-dimensional multinomial distribution is recovered for the sums, which approach a d-dimensional Gaussian distribution for N -> infinity. For any nu, the conditional distributions of the d-dimensional model are shown to yield the corresponding joint distribution of the (d-1)-dimensional model with the same nu. For the d = 2 case, we study the joint probability distribution and identify two classes of marginal distributions, one of them being asymmetric and dimension scale-invariant, while the other one is symmetric and only asymptotically dimension scale-invariant. The present probabilistic model is proposed as a testing ground for a deeper understanding of the necessary and sufficient conditions for having q-Gaussian attractors in the N -> infinity limit, the ultimate goal being a neat mathema! tical view of the causes clarifying the ubiquitous emergence o! f q-stat istics verified in many natural, artificial, and social systems.