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An expansion for the distribution function of a random sum

Published online by Cambridge University Press:  14 July 2016

L. M. Marsh*
Affiliation:
James Cook University of North Queensland

Abstract

The Edgeworth expansion gives an indication of the rate of convergence of the distribution function of the sum of a fixed number of random variables to the normal distribution. A similar expansion is given here for the distribution function of the sum of a random number N of random variables, when the probability generating function of N takes a special form.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1973 

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References

Blum, J. R., Hanson, D. L. and Rosenblatt, J. I. (1963) On the central limit theorem for the sum of a random number of independent random variables. Z. Wahrscheinlichkeitsth. 1, 389393.Google Scholar
Feller, W. (1971) An Introduction to Probability Theory and its Applications. Vol. 2, 2nd ed. Wiley, New York.Google Scholar
Heyde, C. C. and Brown, B. M. (1971) Invariance principles and some convergence rate results for branching processes. Z. Wahrscheinlichkeitsth. 20, 271278.Google Scholar
Heyde, C. C. and Seneta, E. (1971) Analogues of classical limit theorems for the supercritical Galton-Watson process with immigration. Math. Biosci. 11, 249259.Google Scholar
Pyke, R. (1960) On centering infinitely divisible processes. Ann. Math. Statist. 31, 797800.CrossRefGoogle Scholar
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.CrossRefGoogle Scholar
Robbins, H.E. (1948) The asymptotic distribution of the sum of a random number of random variables. Bull. Amer. Math. Soc. 54, 11511161.Google Scholar
Teicher, H. (1954) On the convolution of distributions. Ann. Math. Statist. 25, 775778.Google Scholar
Tomko, J. (1972) The rate of convergence in limit theorems for service systems with finite queue capacity. J. Appl. Prob. 9, 87102.CrossRefGoogle Scholar