Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-20T10:15:11.312Z Has data issue: false hasContentIssue false

Moments for a general branching process in a semi-Markovian environment

Published online by Cambridge University Press:  14 July 2016

Craig Whittaker*
Affiliation:
Texas A&M University
Richard M. Feldman*
Affiliation:
Texas A&M University
*
Postal address: Department of Industrial Engineering, Biosystems Research Division, Texas A&M University, College Station, TX 77843, U.S.A.
Postal address: Department of Industrial Engineering, Biosystems Research Division, Texas A&M University, College Station, TX 77843, U.S.A.

Abstract

A general branching process is extended to allow life length and reproduction probabilities to depend on randomly changing environmental states. First and second moments of the population size with respect to time are derived assuming that the environmental process is semi-Markovian. The results are similar to Markov-renewal type equations which allow, under discrete time, iterative computation of both moments of the population through time.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1980 

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.)

Footnotes

This work was funded in part by a U.S. Department of Agriculture sponsored program entitled ‘The Expanded Southern Pine Beetle Research and Applications Program' Grant Number 89–106 (19–258) and in part by the National Science Foundation and the Environmental Protection Agency, through a Grant (NSF GB-34718) to the University of California.

References

Allen, J. C. (1976) A modified sine wave method for calculating degree days. Environ. Entomol. 5, 388396.Google Scholar
Athreya, K. B. and Karlin, S. (1971) On branching processes with random environments, I: Extinction probabilities. Ann. Math. Statist. 42, 14991520.CrossRefGoogle Scholar
Curry, G. L., Feldman, R. M. and Sharpe, P. J. H. (1978a) Foundations of stochastic development. J. Theoret. Biol. Google Scholar
Curry, G. L., Feldman, R. M. and Smith, K. C. (1978b) A stochastic model of a temperature dependent population. Theoret. Population Biol. 13, 197213.CrossRefGoogle ScholarPubMed
Harris, T. E. (1963) The Theory of Branching Processes. Springer, Berlin.CrossRefGoogle Scholar
Jagers, P. (1974) Galton-Watson processes in varying environments. J. Appl. Prob. 11, 174178.CrossRefGoogle Scholar
Jagers, P. (1975) Branching Processes with Biological Applications. Wiley, London.Google Scholar
Sevastyanov, B. A. (1964) Age-dependent branching processes. Theory Prob. Appl. 9, 521537.CrossRefGoogle Scholar
Sharpe, P. J. H., Curry, G. L., Demichele, D. W. and Cole, C. L. (1977) Distribution model of organism development times. J. Theoret. Biol. 66, 2138.CrossRefGoogle ScholarPubMed
Smith, W. L. and Wilkinson, W. E. (1969) On branching processes in random environments. Ann. Math. Statist. 40, 814827.CrossRefGoogle Scholar
Stinner, R. E., Gutierrez, A. P. and Butler, G. D. (1974) An algorithm for temperature-dependent growth rate simulation. Canadian Entomol. 106, 519524.CrossRefGoogle Scholar
Tanny, D. (1977) Limit theorems for branching processes in a random environment. Ann. Prob. 5, 100116.CrossRefGoogle Scholar