On tail behavior of infinite sums of independent indicators

Let Y=∑k≥11Ak be an infinite sum of the indicators of independent events. We investigate a precise (as opposed to logarithmic) first-order asymptotic behavior of the tail probabilities P{Y≥n} and the point probabilities P{Y=n} as n→∞. Our analysis provides a reasonably complete classification of the asymptotic behaviors covering most cases of practical interest. These general results are then applied to specific examples where the success probabilities rk:=P(Ak) decay polynomially rk∼ck−β or (sub-, super-) exponentially rk∼ce−kβ, yielding the asymptotic tail and point probabilities in explicit forms. As briefly discussed in the paper, infinite sums of independent indicators arise naturally in numerous settings as diverse as the range of Poissonized samples, the infinite Ginibre point processes and decoupled renewal processes, and records in the Fα scheme. We also explore connections between our results and the theory of Hayman-admissible functions, total positivity, and the Laguerre-Pólya class of type I.