Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-27T12:54:53.405Z Has data issue: false hasContentIssue false

On the limit of the Markov binomial distribution

Published online by Cambridge University Press:  14 July 2016

Y. H. Wang*
Affiliation:
Concordia University
*
Postal address: Department of Mathematics, Concordia University, 1455 de Maisonneuve Blvd. W, Montreal H3G 1M8, Canada.

Abstract

Let X1X2, · ·· be a Markov Bernoulli sequence with initial probabilities p of success and q = 1 – p of failure, and probabilities 1 – (1 – π) p, (1 – π) p in the first row and (1 – π) (1 – p), (1 – π) p + πin the second row of the transition matrix. If we define Sn = Σi=1nXi, then the limit distribution P{Sn = k} is obtained when n →∞, np →λ.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1981 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Chen, L. H. Y. (1975) Poisson approximation for dependent trials. Ann. Prob. 3, 535545.Google Scholar
[2] Devore, J. L. (1976) A note on the estimation of parameters in a Bernoulli model with dependence. Ann. Statist. 4, 990992.Google Scholar
[3] Edwards, A. W. F. (1960) The meaning of binomial distribution. Nature, London 186, 1074.Google Scholar
[4] Johnson, N. L. and Kotz, S. (1969) Distributions in StatisticsDiscrete Distributions. Houghton Mifflin, Boston.Google Scholar
[5] Klotz, J. (1972) Markov chain clustering of births by sex. Proc. 6th Berkeley Symp. Math. Statist. Prob. 4, 173185.Google Scholar
[6] Klotz, J. (1973) Statistical inference in Bernoulli trials with dependence. Ann. Statist. 1, 373379.Google Scholar
[7] Moore, M. (1976) Comparison of estimators for the parameter in Bernoulli trials with a persistence indicator. Rapport technique ER76-R-8, Ecole Polytechnique, Montréal.Google Scholar
[8] Moore, M. (1979) Alternatives aux estimateurs à vraisemblance maximale dans un modèle de Bernoulli avec dépendance. Ann. Sci. Math. Quebec 3, 119133.Google Scholar
[9] Pedler, P. J. (1980) Effect of dependence on the occupation time in a two-state stationary Markov chain. J. Amer. Statist. Assoc. 75, 739746.Google Scholar
[10] Switzer, P. (1967) Reconstructing patterns from sample data. Ann. Math. Statist. 38, 138154.Google Scholar
[11] Switzer, P. (1971) Mapping a geographically correlated environment. Proc. 1969 Intl. Symp. on Statistical Ecology Yale University 1, 235270.Google Scholar