Let η={η(t);t∈[0,1]} be a mean zero continuous Gaussian process with covariance U={U(s,t),s,t∈[0,1]}, with U(0,0)>0. Let {ηi;i=1,…,k} be independent copies of η and set Yk(t)=∑i=1kηi2(t),t∈[0,1]. The stochastic process Yk={Yk(t),t∈[0,1]} is referred to as a chi--square process of order k with kernel U. Let ϕ(t) be a positive function on [0,δ] for some δ>0. If t→0limsupϕ(t)η(t)−η(0)=1a.s., then for all integers k≥1, t→0limsupϕ(t)Yk(t)−Yk(0)=2Yk1/2(0)a.s. Set σ2(u,v)=E(η(u)−η(v))2andσ2(x)=∣u−v∣≤xsupσ2(u,v). Assume that inft∈[0,1]U(t,t)>0 and, x→0limσ2(x)log1/x=0. Let φ(t) be a positive function on [0,1]. Then if h→0limu,v∈Δ∣u−v∣≤hsupφ(∣u−v∣)η(u)−η(v)=1a.s. for all intervals Δ⊂[0,1], it follows that for all intervals Δ⊂[0,1] and all integers k≥1, h→0limu,v∈Δ∣u−v∣≤hsupφ(∣u−v∣)Yk(u)−Yk(v)=2u∈ΔsupYk1/2(u),a.s.
@article{arxiv.2106.00542,
title = {Local and uniform moduli of continuity of chi--square processes},
author = {Michael B. Marcus and Jay Rosen},
journal= {arXiv preprint arXiv:2106.00542},
year = {2021}
}
Comments
11 pages. arXiv admin note: text overlap with arXiv:2006.14457