The combinatorics of weighted vector compositions

A vector composition of a vector $\ell$ is a matrix $\mathbf{A}$ whose rows sum to $\ell$. We define a weighted vector composition as a vector composition in which the column values of $\mathbf{A}$ may appear in different colors. We study vector compositions from different viewpoints: (1) We show how they are related to sums of random vectors and (2) how they allow to derive formulas for partial derivatives of composite functions. (3) We study congruence properties of the number of weighted vector compositions, for fixed and arbitrary number of parts, many of which are analogous to those of ordinary binomial coefficients and related quantities. Via the Central Limit Theorem and their multivariate generating functions, (4) we also investigate the asymptotic behavior of several special cases of numbers of weighted vector compositions. Finally, (5) we conjecture an extension of a primality criterion due to Mann and Shanks in the context of weighted vector compositions.

Keywords

vector composition, weighted composition, sum of random variables, partial derivatives, congruences

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Received 7 October 2017

Published 25 January 2019