English

A Compound Poisson Convergence Theorem for Sums of $m$-Dependent Variables

Statistics Theory 2014-02-04 v1 Statistics Theory

Abstract

We prove the Simons-Johnson theorem for the sums SnS_n of mm-dependent random variables, with exponential weights and limiting compound Poisson distribution \CP(s,λ)\CP(s,\lambda). More precisely, we give sufficient conditions for k=0\eehk\abP(Sn=k)\CP(s,λ){k}0\sum_{k=0}^\infty\ee^{hk}\ab{P(S_n=k)-\CP(s,\lambda)\{k\}}\to 0 and provide an estimate on the rate of convergence. It is shown that the Simons-Johnson theorem holds for weighted Wasserstein norm as well. %limiting sum of two Poisson variables defined on %different lattices. The results are then illustrated for N(n;k1,k2)N(n;k_1,k_2) and kk-runs statistics.

Keywords

Cite

@article{arxiv.1402.0183,
  title  = {A Compound Poisson Convergence Theorem for Sums of $m$-Dependent Variables},
  author = {V. Cekanavicius and P. Vellaisamy},
  journal= {arXiv preprint arXiv:1402.0183},
  year   = {2014}
}

Comments

to appear in Journal of Theoretical Probability