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A simple proof of a random stable limit theorem

Published online by Cambridge University Press:  14 July 2016

Stephen R. Kimbleton*
Affiliation:
University of Michigan

Extract

Random stable limit theorems have been obtained by several authors, e.g., [3], [4]. The purpose of this note is to give a rather elementary proof of the basic version of this theorem. Our proof may be viewed as the natural extension to stable laws of the method used by Rényi [2] in obtaining a random central limit theorem. Indeed, the only “outside” theorems used are Kolmogorov's inequality (which Rényi also uses) and a general theorem on necessary and sufficient conditions for convergence of a triangular array. It will also be observed that in the present theorem, the consideration of random variables in the domain of attraction of a stable law of index α = 1, introduces no additional difficulties.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1970 

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References

[1] Gnedenko, B. V. and Kolmogorov, A. N. (1954) Limit Distributions for Sums of Independent Random Variables. Translated and annotated by Chung, K. L. Addison Wesley, Reading, Mass. Google Scholar
[2] Rényi, A. (1957) On the asymptotic distribution of the sum of a random number of independent random variables. Acta Math. Acad. Sci. Hung. 8, 193199.Google Scholar
[3] Teicher, H. (1965) On random sums of random vectors. Ann. Math. Statist. 36, 14501458.Google Scholar
[4] Wittenberg, H. (1964) Limiting distributions of random sums of independent random variables. Z. Wahrscheinlichkeitsth. 3, 718.Google Scholar