A bound on the 2-Wasserstein distance between linear combinations of independent random variables

Abstract

We provide a bound on a natural distance between finitely and infinitely supported elements of the unit sphere of ${\ell }^2({\mathbb{N}}^{\ast })$, the space of real valued sequences with finite ${\ell }^2$ norm. We use this bound to estimate the 2-Wasserstein distance between random variables which can be represented as linear combinations of independent random variables. Our results are expressed in terms of a discrepancy measure which is related to Nourdin and Peccati's Malliavin-Stein method. The main area of application of our results is towards the computation of quantitative rates of convergence towards elements of the second Wiener chaos. After particularizing our bounds to this setting and comparing them with the available literature on the subject (particularly the Malliavin-Stein method for Variance-gamma random variables), we illustrate their versatility by tackling three examples: chi-squared approximation for second order $U$-statistics, asymptotics for sequences of quadratic forms and the behavior of the generalized Rosenblatt process at extreme critical exponent.

New section containing lower bounds

References in corpus (3)

• Central limit theorems for sequences of multiple stochastic integrals
• Chaos of a Markov operator and the fourth moment condition
• Convergence towards linear combinations of chi-squared random variables: a Malliavin-based approach

Cited by in corpus (5)

• Malliavin-Stein Method: a Survey of Recent Developments
• Stein characterizations for linear combinations of gamma random variables
• New moments criteria for convergence towards normal product/tetilla laws
• On the Rate of Convergence to a Gamma Distribution on Wiener Space
• Stein operators for variables form the third and fourth Wiener chaoses