Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-23T05:49:40.406Z Has data issue: false hasContentIssue false

Moment computations for subcritical branching processes

Published online by Cambridge University Press:  14 July 2016

Kenneth Lange*
Affiliation:
University of California, Los Angeles
Michael Boehnke*
Affiliation:
University of California, Los Angeles
Richard Carson*
Affiliation:
University of California, Los Angeles
*
Postal address: Department of Biomathematics, University of California, Los Angeles, CA 90024, U.S.A.
Postal address: Department of Biomathematics, University of California, Los Angeles, CA 90024, U.S.A.
Postal address: Department of Biomathematics, University of California, Los Angeles, CA 90024, U.S.A.

Abstract

The present paper considers methods for computing moments connected with subcritical multitype branching processes. By stressing the interplay between moment and cumulant structure, it is possible to prove simultaneously the existence of the moments. The kinds of moments considered are those arising in (1) times to extinction, (2) ultimate numbers of particles starting from a single particle, and (3) equilibrium numbers of particles for subcritical processes experiencing immigration.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 

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

Research supported in part by the University of California, Los Angeles; NIH Research Career Development Grant K04 HD00307; and NRSA Training Grant GM 7191.

References

Bellman, R. (1970) Introduction to Matrix Analysis, 2nd edn. McGraw-Hill, New York.Google Scholar
Berge, C. (1971) Principles of Combinatorics. Academic Press, New York.Google Scholar
Billingsley, P. (1968) Convergence of Probability Measures. Wiley, New York.Google Scholar
Bodmer, W. F. and Cavalli-Sforza, L. L. (1976) Genetics, Evolution, and Man. Freeman, San Francisco.Google Scholar
Brillinger, D. R. (1969) The calculations of cumulants via conditioning. Ann. Inst. Statist. Math. 21, 215218.Google Scholar
Brillinger, D. R. (1975) Time Series: Data Analysis and Theory. Holt, Rinehart and Winston, New York.Google Scholar
Feller, W. (1971) An Introduction to Probability Theory and its Applications, Vol. 2, 3rd edn. Wiley, New York.Google Scholar
Gladstien, K. and Lange, K. (1978a) Number of people and number of generations affected by a single deleterious mutation. Theoret. Popn. Biol. 14, 313321.CrossRefGoogle ScholarPubMed
Gladstien, K. and Lange, K. (1978b) Equilibrium distributions for deleterious genes in large stationary populations. Theoret. Popn. Biol. 14, 322328.CrossRefGoogle ScholarPubMed
Good, I. J. (1960) Generalizations to several variables of Lagrange's expansion, with applications to stochastic processes. Proc. Camb. Phil. Soc. 56, 367380.Google Scholar
Harris, T. E. (1963) The Theory of Branching Processes. Springer-Verlag, New York.CrossRefGoogle Scholar
Heathcote, C. R. (1965) A branching process allowing immigration. J. R. Statist. Soc. B 27, 138143.Google Scholar
Hewitt, E. and Stromberg, K. (1965) Real and Abstract Analysis. Springer-Verlag, New York.Google Scholar
Hofbauer, J. (1979) A short proof of the Lagrange-Good formula. Discrete Math. 25, 135139.Google Scholar
Jagers, P. (1975) Branching Processes with Biological Applications. Wiley, New York.Google Scholar
Karlin, S. and Taylor, H. M. (1975) A First Course in Stochastic Processes, 2nd edn. Academic Press, New York.Google Scholar
Lange, K., Gladstien, K. and Zatz, M. (1978) Effects of reproductive compensation and genetic drift on X-linked lethals. Amer. J. Hum. Genet. 30, 180189.Google Scholar
Lange, K. and Gladstien, K. (1979) Further characterization of the long-run population distribution of a deleterious gene. Theoret. Popn. Biol. CrossRefGoogle Scholar
Leonov, V. P. and Shiryaev, A. N. (1959) On a method of calculation of semi-invariants. Theory Prob. Appl. 4, 319328.Google Scholar
Nei, M. (1971a) Extinction time of deleterious mutant genes in large populations. Theoret. Popn. Biol. 2, 419425.Google Scholar
Nei, M. (1971b) Total number of individuals affected by a single deleterious mutation in large populations. Theoret. Popn. Biol. 2, 426430.Google Scholar
Ortega, J. M. (1972) Numerical Analysis: A Second Course. Academic Press, New York.Google Scholar
Otter, R. (1949) The multiplicative process. Ann. Math. Statist. 20, 206224.CrossRefGoogle Scholar
Pollard, J. H. (1975) Mathematical Models for the Growth of Human Populations. Cambridge University Press.Google Scholar
Quine, M. P. (1970) The multi-type Galton-Watson process with immigration. J. Appl. Prob. 7, 411422.Google Scholar
Roman, S. M. and Rota, G.-C. (1978) The umbral calculus. Adv. Math. 27, 95188.Google Scholar
Skellam, J. G. (1949) The probability distribution of gene-differences in relation to selection, mutation, and random extinction. Proc. Camb. Phil. Soc. 45, 364367.Google Scholar