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

preprint2020arXivOpen access

Abstract

This paper studies the asymptotic distribution of descents $\des(w)$ in a permutation ww, 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 qq. The main results are a Berry-Esseen theorem for $\des(w)+\des(w^{-1})$ as well as a joint central limit theorem for $(\des(w),\des(w^{-1}))$ to a bivariate normal with a non-trivial correlation depending on qq. The proof uses Stein's method with size-bias coupling along with a regenerative process associated to the Mallows measure.

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