An extension of the Hoeffding inequality to unbounded random variables

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作者
V. Bentkus
机构
[1] Institute of Mathematics and Informatics,
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关键词
Hoeffding’s inequalities; probabilities of large deviations; bounds for tail probabilities; bounded and unbounded random variables; supermartingales;
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摘要
Let S = X1 + ⋯ + Xn be a sum of independent random variables such that 0 ⩽ Xk ⩽ 1 for all k. Write p = E S/n and q = 1 − p. Let 0 < t < q. In this paper, we extend the Hoeffding inequality [16, Theorem 1] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathbb{P}\left\{ {S \geqslant nt + np} \right\} \leqslant H^n \left( {t,p} \right), {\rm H}\left( {t,p} \right) = \left( {\frac{p} {{p + t}}} \right)^{p + t} \left( {\frac{q} {{q - t}}} \right)^{q - t} , $$\end{document}, to the case where Xk are unbounded positive random variables. Our inequalities reduce to the Hoeffding inequality if 0 ⩽ Xk ⩽ 1. Our conditions are Xk ⩾ 0 and E S < ∞. We also provide improvements comparable with the inequalities of Bentkus [5]. The independence of Xk can be replaced by supermartingale-type assumptions. Our methods can be extended to prove counterparts of other inequalities of Hoeffding [16] and Bentkus [5].
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页码:137 / 157
页数:20
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