Precise Large Deviations for Sums of Independent Random Variables with Consistently Varying Tails

Abstract

In this article, we investigate the precise large deviations for a sum of independent but not identical distributed random variables. {X n , n ≥ 1} are independent non-negative random variables with distribution functions {F n , n ≥ 1}. We assume that the average of right tails of distribution functions F n is equivalent to some distribution function F with consistently varying tails. In applications, we apply our main results to a realistic example (Pareto-type distribution) and obtain a specific result.