Saddlepoint Approximations of Cumulative Distribution Functions of Sums of Random Vectors

被引:0
|
作者
Anade, Dadja [1 ]
Gorce, Jean-Marie [1 ]
Mary, Philippe [4 ]
Perlaza, Samir M. [2 ,3 ]
机构
[1] Lab CITI, Villeurbanne, France
[2] INRIA, Ctr Rech Sophia Antipolis Mediterranee, Inria, France
[3] Princeton Univ, Elect Engn Dept, Princeton, NJ 08544 USA
[4] Lab IETR, Rennes, France
来源
2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT) | 2021年
关键词
TAIL PROBABILITY;
D O I
10.1109/ISIT45174.2021.9518101
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, a real-valued function that approximates the cumulative distribution function (CDF) of a finite sum of real-valued independent and identically distributed random vectors is presented. The approximation error is upper bounded by an expression that is easy to calculate. As a byproduct, an upper bound and a lower bound on the CDF are obtained. Finally, in the case of lattice and absolutely continuous random variables, the proposed approximation is shown to be identical to the saddlepoint approximation of the CDF.
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页码:778 / 783
页数:6
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