English

On the error bound in a combinatorial central limit theorem

Probability 2015-04-14 v5 Statistics Theory Statistics Theory

Abstract

Let X={Xij:1i,jn}\mathbb{X}=\{X_{ij}: 1\le i,j\le n\} be an n×nn\times n array of independent random variables where n2n\ge2. Let π\pi be a uniform random permutation of {1,2,,n}\{1,2,\dots,n\}, independent of X\mathbb{X}, and let W=i=1nXiπ(i)W=\sum_{i=1}^nX_{i\pi(i)}. Suppose X\mathbb{X} is standardized so that EW=0,Var(W)=1{\mathbb{E}}W=0,\operatorname {Var}(W)=1. We prove that the Kolmogorov distance between the distribution of WW and the standard normal distribution is bounded by 451i,j=1nEXij3/n451\sum_{i,j=1}^n{\mathbb{E}}|X_{ij}|^3/n. Our approach is by Stein's method of exchangeable pairs and the use of a concentration inequality.

Keywords

Cite

@article{arxiv.1111.3159,
  title  = {On the error bound in a combinatorial central limit theorem},
  author = {Louis H. Y. Chen and Xiao Fang},
  journal= {arXiv preprint arXiv:1111.3159},
  year   = {2015}
}

Comments

Published at http://dx.doi.org/10.3150/13-BEJ569 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

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