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Bayes' Estimation of the Number of Component Processes of a Superimposed Process

Published online by Cambridge University Press:  27 July 2009

Olga S. Yoshida
Affiliation:
Departamento de Estatistica – IME, Universidade de Sāo Paulo, Caixa Postal 20570–CEP 05389-970 São Paulo, Brazil
José G. Leite
Affiliation:
Departamento de Estatistica – IME, Universidade de Sāo Paulo, Caixa Postal 20570–CEP 05389-970 São Paulo, Brazil
Heleno Bolfarine
Affiliation:
Departamento de Estatistica – IME, Universidade de Sāo Paulo, Caixa Postal 20570–CEP 05389-970 São Paulo, Brazil

Abstract

We consider Bayes' estimation of the number of independent homogeneous Poisson processes of a superimposed process with unknown rates. The estimation of the total rate of the undetected processes is also considered. Exact posterior distributions are obtained. Monotonicity and asymptotic properties of the Bayes' estimator are also discussed.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1996

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References

1.Lehmann, E.L. (1966). Some concepts of dependence. Annals of Mathematical Statistics 37: 11371153.CrossRefGoogle Scholar
2.Nayak, T.K. (1988). Estimating population size by recapture sampling. Biometrika 75: 113120.CrossRefGoogle Scholar
3.Nayak, T.K. (1989). A note on estimating the number of errors in a system by recapture sampling. Statistics and Probability Letters 7: 9194.Google Scholar
4.Nayak, T.K. (1991). Estimating the number of component processes of a superimposed process. Biometrika 78: 7581.CrossRefGoogle Scholar
5.Nayak, T.K. (1993). On estimating the total rate of the unobserved processes. Statistics and Probability Letters 17: 351354.CrossRefGoogle Scholar
6.Ross, S.M. (1985). Statistical estimation of software reliability. IEEE Transactions on Software Engineering SE-11(5): 479483.CrossRefGoogle Scholar
7.Ross, S.M. (1985). Software reliability; the stopping rule problem. IEEE Transactions on Software Engineering SE-11(12): 14721476.CrossRefGoogle Scholar