A central limit theorem for descents of a Mallows permutation and its inverse

Abstract

This paper studies the asymptotic distribution of descents (w) in a permutation w, and its inverse, distributed according to the Mallows measure. The Mallows measure is a non-uniform probability measure on permutations introduced to study ranked data. Under this measure, permutations are weighted according to the number of inversions they contain, with the weighting controlled by a parameter q. The main results are a Berry-Esseen theorem for (w)+(w-1) as well as a joint central limit theorem for ((w),(w-1)) to a bivariate normal with a non-trivial correlation depending on q. The proof uses Stein's method with size-bias coupling along with a regenerative process associated to the Mallows measure.

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