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Statistics & Probability Letters
Article . 2012 . Peer-reviewed
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Article . 2012
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https://dx.doi.org/10.48550/ar...
Article . 2011
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Majorization bounds for distribution functions

Authors: Bairamov, Ismihan;

Majorization bounds for distribution functions

Abstract

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

Related Organizations
Keywords

62G30, order statistics, concomitants, majorization, FOS: Mathematics, Inequalities; stochastic orderings, Probability distributions: general theory, Mathematics - Statistics Theory, Statistics Theory (math.ST)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green