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Comparing sums of exchangeable Bernoulli random variables

Published online by Cambridge University Press:  14 July 2016

Claude Lefèvre*
Affiliation:
Université Libre de Bruxelles
Sergey Utev*
Affiliation:
Novosibirsk University
*
Postal address: Institut de Statistique, CP 210, Université Libre de Bruxelles, Boulevard du Triomphe, B-1050 Bruxelles, Belgique.
∗∗Postal address: Institute of Mathematics, Universitetsky pr. 4, Novosibirsk 630090, Russia.

Abstract

The paper is first concerned with a comparison of the partial sums associated with two sequences of n exchangeable Bernoulli random variables. It then considers a situation where such partial sums are obtained through an iterative procedure of branching type stopped at the first-passage time in a linearly decreasing upper barrier. These comparison results are illustrated with applications to certain urn models, sampling schemes and epidemic processes. A key tool is a non-standard hierarchical class of stochastic orderings between discrete random variables valued in {0, 1,· ··, n}.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1996 

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Footnotes

Research partially supported by the Fonds National de la Recherche Scientifique Belge.

References

Bailey, N. T. J. (1975) The Mathematical Theory of Infectious Diseases and its Applications. Griffin, London.Google Scholar
De Finetti, B. (1937) La prévision: ses lois logiques, ses sources subjectives. Ann. Inst. H. Poincaré 7, 168.Google Scholar
Frechet, M. (1943) Les probabilités associées à un système d'evènements compatibles et dépendants. Actualités Sci. Industr. 942. Hermann, Paris.Google Scholar
Kendall, D. G. (1967) On finite and infinite sequences of exchangeable events. Studia Sci. Math. Hungar. 2, 319327.Google Scholar
Kissami, A., Lefevre, Cl. and Picard, Ph. (1994) On collective epidemic models and (partially) exchangeable events. Cahiers Centre Etudes Rech. Opérat. 36, 235250.Google Scholar
Lefevre, Cl. (1994) Stochastic ordering of epidemics. In Stochastic Orders and their Applications , ed. Shaked, M. and Shanthikumar, J. G. pp. 323348. Academic Press, New York.Google Scholar
Lefevre, Cl. and Picard, Ph. (1989) On the formulation of discrete-time epidemic models. Math. Biosci. 95, 2735.Google Scholar
Lefevre, Cl. and Picard, Ph. (1993) An unusual stochastic order relation with some applications in sampling and epidemic theory. Adv. Appl. Prob. 25, 6381.Google Scholar
Martin-Löf, A. (1986) Symmetric sampling procedures, general epidemic processes and their threshold limit theorems. J. Appl. Prob. 23, 265282.Google Scholar
Picard, Ph. and Lefevre, Cl. (1990) A unified analysis of the final size and severity distribution in collective Reed-Frost epidemic processes. Adv. Appl. Prob. 22, 269294.Google Scholar
Samuel, E. (1968) Sequential maximum likelihood estimation of the size of a population. Ann. Math. Statist. 39, 10571068.Google Scholar
Scarsini, M. (1994) Comparing risk and risk aversion. In Stochastic Orders and their Applications , ed. Shaked, M. and Shanthikumar, J. G. pp. 351378. Academic Press, New York.Google Scholar
Shaked, M. and Shanthikumar, J. G. (1994) Stochastic Orders and their Applications. Academic Press, New York.Google Scholar
Stoyan, D. (1983) Comparison Methods for Queues and Other Stochastic Models. Wiley, New York.Google Scholar
Von Bahr, B. and Martin-Löf, A. (1980) Threshold limit theorems for some epidemic processes. Adv. Appl. Prob. 12, 319349.Google Scholar