Up-smooth Samples of Geometric Variables

Arnold Knopfmacher1, Toufik Mansour2
1The John Knopfmacher Centre for Applicable Analysis and Number Theory, School of Mathematics University of the Witwatersrand, Johannesburg, South Africa
2Department of Mathematics University of Haifa, 31905 Haifa, Israel

Abstract

We study samples \(\Gamma = (\Gamma_1, \ldots, \Gamma_n)\) of length \(n\) where the letters \(\Gamma_i\) are independently generated according to the geometric distribution \(\mathbb{P}(\Gamma_j = i) = pq^{i-1}\), for \(1 \leq j \leq n\), with \(p+q=1\) and \(0<p<1\). An \({up-smooth\; sample}\) \(\Gamma\) is a sample such that \(\Gamma_{i+1}- \Gamma_i \leq 1\). We find generating functions for the probability that a sample of \(n\) geometric variables is up-smooth, with or without a specified first letter. We also extend the up-smooth results to words over an alphabet of \(k\) letters and to compositions of integers. In addition, we study smooth samples \(T\) of geometric random variables, where the condition now is \(|\Gamma_{i+1}- \Gamma_i| \leq 1\).