English

Majorization bounds for distribution function

Statistics Theory 2011-09-02 v1 Statistics Theory

Abstract

Let XX be a random variable with distribution function F,F, and X1,X2,...,XnX_{1},X_{2},...,X_{n} are independent copies of X.X. Consider the order statistics Xi:n,X_{i:n}, i=1,2,...,ni=1,2,...,n and denote Fi:n(x)=P{Xi:nx}.F_{i:n}(x)=P\{X_{i:n}\leq x\}. Using majorization theory we write upper and lower bounds for FF expressed in terms of mixtures of distribution functions of order statistics, i.e. i=1npiFi:n\sum \limits_{i=1}^{n}p_{i}F_{i:n} and i=1npiFni+1:n.\sum \limits_{i=1}^{n}p_{i}F_{n-i+1:n}. It is shown that these bounds converge to FF \ for a particular sequence (p1(m),p2(m),...,pn(m)),m=1,2,..(p_{1}(m),p_{2}(m),...,p_{n}(m)),m=1,2,.. as m.m\rightarrow\infty.

Keywords

Cite

@article{arxiv.1109.0141,
  title  = {Majorization bounds for distribution function},
  author = {Ismihan Bairamov},
  journal= {arXiv preprint arXiv:1109.0141},
  year   = {2011}
}
R2 v1 2026-06-21T18:58:17.301Z