Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-25T12:38:18.262Z Has data issue: false hasContentIssue false

Asymptotic behavior of Markov systems

Published online by Cambridge University Press:  14 July 2016

P.-C. G. Vassiliou*
Affiliation:
University of Ioannina
*
Postal address: Department of Mathematics, University of Ioannina, Ioannina, Greece. Part of this work was done while the author was at Imperial College, London.

Abstract

In this paper we study the asymptotic behavior of Markov systems and especially non-homogeneous Markov systems. It is found that the limiting structure and the relative limiting structure exist under certain conditions. The problem of weak ergodicity in the above non-homogeneous systems is studied. Necessary and sufficient conditions are provided for weak ergodicity. Finally, we discuss the application of the present results in manpower systems.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1982 

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

Bartholomew, D. J. (1971) The statistical approach to manpower planning. Statistician 20, 326.CrossRefGoogle Scholar
Bartholomew, D. J. (1973) Stochastic Models for Social Processes, 2nd edn. Wiley, New York.Google Scholar
Bartholomew, D. J. and Forbes, A. F. (1979) Statistical Techniques for Manpower Planning. Wiley, New York.Google Scholar
Bowerman, B. (1974) Nonstationary Markov Decision Processes and Related Topics in Nonstationary Markov Chains. , Iowa State University.Google Scholar
Coale, A. J. (1957) How the age distribution of a human population is determined. In Cold Spring Harbor Symposium on Quantitative Biology 22, ed. Warren, K. B., Long Island Biological Association, New York, 8389.Google Scholar
Conlisk, J. (1976) Interactive Markov chains. J. Math. Sociol. 14, 157185.Google Scholar
Feichtinger, G. (1976) On the generalization of stable age distributions to Gani type person flow models. Adv. Appl. Prob. 8, 433455.Google Scholar
Feichtinger, G. and Mehlmann, A. (1976) The recruitment trajectory corresponding to particular stock sequences in Markovian person flow models. Math. Operat. Res. 1, 175184.CrossRefGoogle Scholar
Iosifescu, M. (1980) Finite Markov Processes and their Applications. Wiley, New York.Google Scholar
Isaacson, L. D. and Madsen, W. R. (1976) Markov Chains. Wiley, New York.Google Scholar
Lopez, A. (1961) Problems in Stable Population Theory. Office of Population Research, Princeton, NJ.Google Scholar
Pollard, J. H. (1973) Mathematical Models for the Growth of Human Populations. Cambridge University Press, London.Google Scholar
Seneta, E. (1973) Non-Negative Matrices. Allen and Unwin, London.Google Scholar
Vassiliou, P.-C. G. (1976) A Markov chain model for the prediction of wastage in manpower systems. Operat. Res. Quart. 27, 5770.Google Scholar
Vassiliou, P.-C. G. (1978) A high order Markovian model for promotion in manpower systems. J. R. Statist. Soc. A 141, 8694.Google Scholar
Vassiliou, P.-C. G. (1981a) On the limiting behaviour of a nonhomogeneous Markov chain model in manpower systems. Biometrika 68, 557561.Google Scholar
Vassiliou, P.-C. G. (1981b) Stability in a non-homogeneous Markov chain model in manpower systems. J. Appl. Prob. 18, 924930.Google Scholar
Vassiliou, P.-C. G. and Vassiliou, F. P. (1979) On the limiting structure of an expanding Markovian system with given size. Rev. Roum. Math. Pures Appl. XXIV, 11291136.Google Scholar
Young, A. (1971) Demographic and ecological models for manpower planning. In Aspects of Manpower Planning, ed. Bartholomew, D. J. and Smith, A. R., English Universities Press, London, 7597.Google Scholar
Young, A. and Vassiliou, P.-C. G. (1974) A non-linear model on the promotion of staff. J. R. Statist. Soc. A 137, 584595.Google Scholar