A general Hsu-Robbins-Erdos type estimate of tail probabilities of sums of independent identically distributed random variables

Details A general Hsu-Robbins-Erdos type estimate of tail probabilities of sums of independent identically distributed random variables A general Hsu-Robbins-Erdos type estimate of tail probabilities of sums of independent identically distributed random variables

1998-10-28

arxiv.org/abs/math/9810163v1

Mathematics

Probability

Scientific paper

Let X_1,X_2,... be a sequence of independent and identically distributed random variables, and put S_n=X_1+...+X_n. Under some conditions on the positive sequence tau_n and the positive increasing sequence a_n, we give necessary and sufficient conditions for the convergence of sum_{n=1}^infty tau_n P(|S_n|>t a_n) for all t>0, generalizing Baum and Katz's (1965) generalization of the Hsu-Robbins-Erdos (1947, 1949) law of large numbers, also allowing us to characterize the convergence of the above series in the case where tau_n=1/n and a_n=(n log n)^{1/2} for n>1, thereby answering a question of Spataru. Moreover, some results for non-identically distributed independent random variables are obtained by a recent comparison inequality. Our basic method is to use a central limit theorem estimate of Nagaev (1965) combined with the Hoffman-Jorgensen inequality(1974).

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