Moments of permutation statistics and central limit theorems

TL;DR

This paper explores moments of permutation statistics expressed via bivincular patterns, providing new proofs of CLTs, explicit moment formulas, and insights into asymptotic normality for various permutation statistics.

Contribution

It generalizes previous results by expressing moments as linear combinations of factorials for bivincular pattern statistics and offers new proofs and formulas for permutation statistics.

Findings

Moments of permutation statistics can be expressed as linear combinations of factorials.

A new proof of the CLT for classical pattern occurrences is provided.

Explicit formulas for moments of descents and minimal descents are derived.

Abstract

We show that if a permutation statistic can be written as a linear combination of bivincular patterns, then its moments can be expressed as a linear combination of factorials with constant coefficients. This generalizes a result of Zeilberger. We use an approach of Chern, Diaconis, Kane and Rhoades, previously applied on set partitions and matchings. In addition, we give a new proof of the central limit theorem (CLT) for the number of occurrences of classical patterns, which uses a lemma of Burstein and Hasto. We give a simple interpretation of this lemma and an analogous lemma that would imply the CLT for the number of occurrences of any vincular pattern. Furthermore, we obtain explicit formulas for the moments of the descents and the minimal descents statistics. The latter is used to give a new direct proof of the fact that we do not necessarily have asymptotic normality of the number of pattern occurrences in the case of bivincular patterns. Closed forms for some of the higher moments of several popular statistics on permutations are also obtained.