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

Statistics Theory 2019-06-11 v2 Information Theory math.IT Machine Learning Statistics Theory

Abstract

This note displays an interesting phenomenon for percentiles of independent but non-identical random variables. Let X1,,XnX_1,\cdots,X_n be independent random variables obeying non-identical continuous distributions and X(1)X(n)X^{(1)}\geq \cdots\geq X^{(n)} be the corresponding order statistics. For any p(0,1)p\in(0,1), we investigate the 100(1p)100(1-p)%-th percentile X(pn)X^{(pn)} and prove non-asymptotic bounds for 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 XkN(0,σk2)X_k\sim\mathcal{N}(0,\sigma_k^2) for k=1,,nk=1,\cdots,n and p=12p=\frac{1}{2}, we show that its median Med(X1,,Xn)=OP(n1/2(k=1nσk1)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) as long as {σk}k=1n\{\sigma_k\}_{k=1}^n satisfy certain mild non-dispersion property.

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Cite

@article{arxiv.1808.07997,
  title  = {Non-asymptotic bounds for percentiles of independent non-identical random variables},
  author = {Dong Xia},
  journal= {arXiv preprint arXiv:1808.07997},
  year   = {2019}
}

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14 pages