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  • 标题:Improved Hoeffding’s Lemma and Hoeffding’s Tail Bounds
  • 本地全文:下载
  • 作者:David Hertz
  • 期刊名称:International Journal of Statistics and Probability
  • 印刷版ISSN:1927-7032
  • 电子版ISSN:1927-7040
  • 出版年度:2021
  • 卷号:10
  • 期号:5
  • 页码:27-30
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要:The purpose of this article is to improve Hoeffding’s lemma and consequently Hoeffding’s tail bounds. The improvement pertains to left skewed zero mean random variables X ∈ [a, b], where a b. The proof of Hoeffding’s improved lemma uses Taylor’s expansion, the convexity of exp(sx), s ∈ R, and an unnoticed observation since Hoeffding’s publication in 1963 that for −a > b the maximum of the intermediate function τ(1 − τ) appearing in Hoeffding’s proof is attained at an endpoint rather than at τ = 0.5 as in the case b > −a. Using Hoeffding’s improved lemma we obtain one sided and two sided tail bounds for P(S n ≥ t) and P( S n ≥ t), respectively, where S n = Pn i=1 Xi and the Xi ∈ [ai , bi], i = 1, ..., n are independent zero mean random variables (not necessarily identically distributed). It is interesting to note that we could also improve Hoeffding’s two sided bound for all {Xi : −ai , bi , i = 1, ..., n}. This is so because here the one sided bound should be increased by P(−S n ≥ t), wherein the left skewed intervals become right skewed and vice versa.
  • 关键词:Hoeffding’s lemma;Hoeffding’s tail bounds;Chernoff’s bound
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