随机变量部分和乘积的渐近分布又称为“算术平均的几何平均”中心极限定理,最先由Arnold和Villasefior(1998)在讨论记录值的和的极限性质时引入,之后便引起了许多学者的研究兴趣.Arnold和Villasefior的结果是针对独立同分布的指数分布随机变量,Rempaa和Wesotowski(2002)将其推广到一般的独立同分布平方可积正值随机变量,并进一步推广至u统计量.Gonchigdanzan和Rempata(2006)讨论了独立同分布随机变量部分和乘积的几乎处处中心极限定理,Gonchigdanzan(2005)给出了U统计量的几乎处处中心极限定理.
Let {Xn, -∞〈 n 〈 ∞} be a sequence of independent and identically distributed, positive, square integrable random variables with # = EX1, cr2 = VarX1 〉 O. The asymptotic properties for the products of a class of statistics (or random functions) expressed by Tn = anS, + Rn are discussed, where Sn = ∑i=1^n Xi, an 〉 0 is a sequence of constants, Rn = o(an√n) i=1 a.s.. The results contain the almost sure central limit theorems, asymptotically lognormality and the weak invariance principles. Some examples such as U-statistics, Von-Mises statistics, error variance estimates in linear models are stated to illustrate the generality of the results.