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Log-concavity and log-convexity in passage time densities of diffusion and birth-death processes

Published online by Cambridge University Press:  14 July 2016

Julian Keilson*
Affiliation:
University of Rochester

Extract

Diffusion and birth-death processes have basic theoretical and practical importance for statistics. Insight into the structure of transition distributions and passage time distributions for such processes has been given in recent years by Feller. Karlin, Kemperman, D. G. Kendall, Reuter and many others. An elementary account of this work and partial bibliography has been given elsewhere ([9], [10)]. Certain key passage time densities and sojourn time densities for such processes have a simple property of log-concavity or log-convexity and associated unimodality. Such properties provide information on the character of distributions unavailable from the spectral representations, Laplace transforms and series of convolutions at hand. These properties may also have value for purposes of estimation and optimization.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1971 

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References

[1] Breiman, L. (1968) Probability. Addison-Wesley, Reading, Mass.Google Scholar
[2] Cox, D. R. and Miller, H. D. (1965) The Theory of Stochastic Processes. Wiley New, York.Google Scholar
[3] Darling, D. A. and Siegert, A. J. F. (1953) The first passage problem for a continuous Markov process. Ann. Math. Statist. 24, 624639.Google Scholar
[4] Feller, W. (1966) Probability Theory and its Applications Vol. II. Wiley, New York.Google Scholar
[5] Feller, W. (1959) The birth and death processes as diffusion processes. J. Math. Pures Appl. 38, 301345.Google Scholar
[6] Ibragimov, I. A. (1956) On the composition of unimodal distributions. Theor. Probability. Appl. 1,CrossRefGoogle Scholar
[7] Karlin, S. (1966) A First Course in Stochastic Processes. Academic Press, New York.Google Scholar
[8] Karlin, S. and Mcgregor, J. L. (1957) The differential equations of birth and death processes and the Stieltjes moment problem. Trans. Amer. Math. Soc. 85, 489546.Google Scholar
[9] Keilson, J. (1964) A review of transient behavior in regular diffusion and birth-death processes. J. Appl. Prob. 1, 247266.CrossRefGoogle Scholar
[10] Keilson, J. (1965) A review of transient behavior in regular diffusion and birth-death processes. Part II. J. Appl. Prob. 2, 405428.Google Scholar
[11] Keilson, J. (1966) A limit theorem for passage times in ergodic regenerative processes. Ann. Math. Statist. 4, 866870.Google Scholar
[12] Kingman, J. F. C. (1961) A convexity property of positive matrices. Quart. J. Math. 12, 283284.Google Scholar
[13] Lederman, W. and Reuter, G. E. H. (1954) Spectral theory for the differential equations of simple birth and death processes. Phil. Trans. 246, 321369.Google Scholar
[14] Miller, H. D. (1967) A note on passage time and infinitely divisible distributions. J. Appl. Prob. 4, 402405.CrossRefGoogle Scholar
[15] Steutel, F. W. (1969) Note on completely monotone densities. Ann. Math. Statist. 40, 11301131.Google Scholar
[16] Stone, C. (1963) Limit theorems for random walks, birth and death processes, and diffusion processes. Illinois J. Math. 7, 638660.CrossRefGoogle Scholar