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Non-asymptotic bounds for percentiles of independent non-identical random variables

24 August 2018
Dong Xia
ArXiv (abs)PDFHTML
Abstract

This note displays an interesting phenomenon for percentiles of independent but non-identical random variables. Let X1,⋯ ,XnX_1,\cdots,X_nX1​,⋯,Xn​ be independent random variables obeying non-identical continuous distributions and X(1)≥⋯≥X(n)X^{(1)}\geq \cdots\geq X^{(n)}X(1)≥⋯≥X(n) be the corresponding order statistics. For any p∈(0,1)p\in(0,1)p∈(0,1), we investigate the 100(1−p)100(1-p)100(1−p)%-th percentile X(pn)X^{(pn)}X(pn) and prove non-asymptotic bounds for X(pn)X^{(pn)}X(pn). In particular, for a wide class of distributions, we discover an intriguing connection between their median and the harmonic mean of the associated standard deviations. For example, if Xk∼N(0,σk2)X_k\sim\mathcal{N}(0,\sigma_k^2)Xk​∼N(0,σk2​) for k=1,⋯ ,nk=1,\cdots,nk=1,⋯,n and p=12p=\frac{1}{2}p=21​, we show that its median ∣Med(X1,⋯ ,Xn)∣=OP(n1/2⋅(∑k=1nσk−1)−1)\big|{\rm Med}\big(X_1,\cdots,X_n\big)\big|= O_P\Big(n^{1/2}\cdot\big(\sum_{k=1}^n\sigma_k^{-1}\big)^{-1}\Big)​Med(X1​,⋯,Xn​)​=OP​(n1/2⋅(∑k=1n​σk−1​)−1) as long as {σk}k=1n\{\sigma_k\}_{k=1}^n{σk​}k=1n​ satisfy certain mild non-dispersion property.

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