Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T12:07:43.122Z Has data issue: false hasContentIssue false

Ladder variables, internal structure of Galton–Watson trees and finite branching random walks

Published online by Cambridge University Press:  14 July 2016

Jean-François Marckert*
Affiliation:
Université de Versailles
Abdelkader Mokkadem*
Affiliation:
Université de Versailles
*
Postal address: Université de Versailles, 45 Avenue des Etats Unis, 78035 Versailles Cedex, France
Postal address: Université de Versailles, 45 Avenue des Etats Unis, 78035 Versailles Cedex, France

Abstract

In this paper, we consider Galton–Watson trees conditioned by size. We show that the number of k-ancestors (ancestors that have k children) of a node u is (almost) proportional to its depth. The k, j-ancestors are also studied. The methods rely on the study of ladder variables on an associated random walk. We also give an application to finite branching random walks.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2003 

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

Aldous, D. (1991). The continuum random tree. II. An overview. In Stochastic Analysis (London Math. Soc. Lecture Notes 167), Cambridge University Press, pp. 2370.Google Scholar
Bennies, J., and Kersting, G. (2000). A random walk approach to Galton–Watson trees. J. Theoret. Prob. 13, 777803.Google Scholar
Duquesne, T., and Le Gall, J.-F. (2002). Random Trees, Lévy Processes and Spatial Branching Processes (Astérisque 281). Société Mathématique de France, Paris.Google Scholar
Feller, W. (1971). An Introduction to Probability Theory and Its Applications, Vol 2, 2nd edn. John Wiley, New York.Google Scholar
Flajolet, P., and Odlyzko, A. (1982). The average height of binary trees and other simple trees. J. Comput. System Sci. 25, 171213.Google Scholar
Harris, T. E. (1952). First passage and recurrence distributions. Trans. Amer. Math. Soc. 73, 471486.Google Scholar
Kendall, D. G. (1951). Some problems in the theory of queues. J. R. Statist. Soc. B. 13, 151185.Google Scholar
Kennedy, D. P. (1976). The distribution of the maximum Brownian excursion. J. Appl. Prob. 13, 371376.Google Scholar
Kolchin, V. F. (1986). Random Mappings (Translation Ser. Math. Eng.). Optimization Software, New York.Google Scholar
Le Gall, J.-F. (2000). Lévy Processes and Branching Processes. Course Notes.Google Scholar
Le Gall, J.-F., and Le Jan, Y. (1998). Branching processes in Lévy processes: the exploration process. Ann. Prob. 26, 213252.Google Scholar
Lyons, R., and Peres, Y. (2002). Probability on trees and networks. Unpublished manuscript. Available at http://mypage.iu.edu/~rdlyons/.Google Scholar
Marckert, J. F., and Mokkadem, A. (2003). The depth first processes of Galton–Watson trees converge to the same Brownian excursion. Ann. Prob. 31, 16551678.Google Scholar
Meir, A., and Moon, J. W. (1978). On the altitude of nodes in random trees. Canad. J. Math. 30, 9971015.CrossRefGoogle Scholar
Otter, R. (1949). The multiplicative process. Ann. Math. Statist. 20, 206224.CrossRefGoogle Scholar
Petrov, V. V. (1995). Limit Theorems of Probability Theory. Oxford University Press.Google Scholar
Port, S. C. (1994). Theoretical Probability for Applications. John Wiley, New York.Google Scholar