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Convergence in law of random sums with non-random centering
Authors:Mark Finkelstein  Victor M. Kruglov  Howard G. Tucker
Affiliation:(1) Department of Mathematics, University of California, 92717 Irvine, California;(2) Department of Mathematics and Cybernetics, Moscow State University, Moscow, Russia
Abstract:We extend results obtained in Kruglov,(7) and Finkelstein and Tucker(3) to obtain necessary and sufficient conditions for convergence in law of random sums of non-identically distributed independent random variables under non-random centering. Thei.i.d. case is also considered for random variables attracted to a stable law. Necessary and sufficient conditions for convergence in law of these random variables under non-random centering, and in some cases, under non-random norming, are also obtained. The distribution functions for the limit laws are determined as well, generalizing results of Robbins.(10)Supported in part by The State University of New York and United States Information Agency Grant No. IA AEMP69193692.
Keywords:Convergence in law  independent random variables  stable law
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