On Asymptotically Tight Tail Bounds for Sums of Geometric and Exponential Random Variables

2019/02/07 by Yaonan Jin, Yingkai Li, Jin, Yaonan +5
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Bayesian Methods and Mixture Models #FOS: Mathematics #Probability and Risk Models #Statistics Theory (math.ST) #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1902.02852

openalex publication_date 2019/02/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this note we prove bounds on the upper and lower probability tails of sums of independent geometric or exponentially distributed random variables. We also prove negative results showing that our established tail bounds are asymptotically tight.

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