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Bounds to the Normal Approximation for Linear Recursions with Two Effects

Probability 2019-11-18 v1

Abstract

Let X0X_0 be a non-constant random variable with finite variance. Given an integer k2k\ge2, define a sequence {Xn}n=1\{X_n\}_{n=1}^\infty of approximately linear recursions with small perturbations {Δn}n=0\{\Delta_n\}_{n=0}^\infty by Xn+1=i=1kan,iXn,i+Δnfor all n0X_{n+1} = \sum_{i=1}^k a_{n,i} X_{n,i} + \Delta_n \quad \text{for all } n\ge0 where Xn,1,,Xn,kX_{n,1},\dots,X_{n,k} are independent copies of the XnX_n and an,1,,an,ka_{n,1},\dots,a_{n,k} are real numbers. In 2004, Goldstein obtained bounds on the Wasserstein distance between the standard normal distribution and the law of XnX_n which is in the form CγnC \gamma^n for some constants C>0C>0 and 0<γ<10 < \gamma < 1. In this article, we extend the results to the case of two effects by studying a linear model Zn=Xn+YnZ_n=X_n+Y_n for all n0n\ge0, where {Yn}n=1\{Y_n\}_{n=1}^\infty is a sequence of approximately linear recursions with an initial random variable Y0Y_0 and perturbations {Λn}n=0\{\Lambda_n\}_{n=0}^\infty, i.e., for some 2\ell \ge2, Yn+1=j=1bn,jYn,j+Λnfor all n0Y_{n+1} = \sum_{j=1}^\ell b_{n,j} Y_{n,j} + \Lambda_n \quad \text{for all } n\ge0 where YnY_n and Yn,1,,Yn,Y_{n,1},\dots,Y_{n,\ell} are independent and identically distributed random variables and bn,1,,bn,b_{n,1},\dots,b_{n,\ell} are real numbers. Applying the zero bias transformation in the Stein\rq s equation, we also obtain the bound for ZnZ_n. Adding further conditions that the two models (Xn,Δn)(X_n,\Delta_n) and (Yn,Λn)(Y_n,\Lambda_n) are independent and that the difference between variance of XnX_n and YnY_n is smaller than the sum of variances of their perturbation parts, our result is the same as previous work.

Keywords

Cite

@article{arxiv.1911.06444,
  title  = {Bounds to the Normal Approximation for Linear Recursions with Two Effects},
  author = {Mongkhon Tuntapthai},
  journal= {arXiv preprint arXiv:1911.06444},
  year   = {2019}
}
R2 v1 2026-06-23T12:16:43.380Z