Arcsine laws for random walks generated from random permutations with applications to genomics. (December 2021)

• Record Type: Journal Article
• Authors: Fang, Xiao; Gan, Han L.; Holmes, Susan; Huang, Haiyan; Peköz, Erol; Röllin, Adrian; Tang, Wenpin
• Is Part Of: Journal of applied probability. Volume 58:Number 4(2021)
• Page Start: 851
• Page End: 867
• Publication Date: 2021-12
• Subjects: Brownian motion -- Lévy statistics -- Mallows permutation -- Stein's method -- strong embedding -- uniform permutation; 60C05 -- 60J65 -- 05A05; 519.2
• DOI: 10.1017/jpr.2021.14
• Languages: English
• ISSNs: 0021-9002

Abstract

Abstract: A classical result for the simple symmetric random walk with 2 n steps is that the number of steps above the origin, the time of the last visit to the origin, and the time of the maximum height all have exactly the same distribution and converge when scaled to the arcsine law. Motivated by applications in genomics, we study the distributions of these statistics for the non-Markovian random walk generated from the ascents and descents of a uniform random permutation and a Mallows( q ) permutation and show that they have the same asymptotic distributions as for the simple random walk. We also give an unexpected conjecture, along with numerical evidence and a partial proof in special cases, for the result that the number of steps above the origin by step 2n for the uniform permutation generated walk has exactly the same discrete arcsine distribution as for the simple random walk, even though the other statistics for these walks have very different laws. We also give explicit error bounds to the limit theorems using Stein's method for the arcsine distribution, as well as functional central limit theorems and a strong embedding of the Mallows( q ) permutation which is of independent interest.