Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-03T02:59:45.722Z Has data issue: false hasContentIssue false
  • English
  • Français

Splitting Trees Stopped when the First Clock Rings and Vervaat's Transformation

Part of: Markov processes Special processes Stochastic processes

Published online by Cambridge University Press:  12 February 2018

Amaury Lambert  and
Pieter Trapman
Amaury Lambert*
Affiliation:
Université Pierre et Marie Curie-Paris 6
Pieter Trapman*
Affiliation:
Stockholm University
*
∗ Postal address: Laboratoire de Probabilités et Modèles Aléatoires, UMR 7599 CNRS, Université Pierre et Marie Curie-Paris 6, case courrier 188, 4 Place Jussieu, F-75252 Paris Cedex 05, France. Email address: [email protected]
∗∗ Postal address: Department of Mathematics, Stockholm University, 106 91 Stockholm, Sweden. Email address: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We consider a branching population where individuals have independent and identically distributed (i.i.d.) life lengths (not necessarily exponential) and constant birth rates. We let Nt denote the population size at time t. We further assume that all individuals, at their birth times, are equipped with independent exponential clocks with parameter δ. We are interested in the genealogical tree stopped at the first time T when one of these clocks rings. This question has applications in epidemiology, population genetics, ecology, and queueing theory. We show that, conditional on {T<∞}, the joint law of (Nt, T, X(T)), where X(T) is the jumping contour process of the tree truncated at time T, is equal to that of (M, -IM, Y′M) conditional on {M≠0}. Here M+1 is the number of visits of 0, before some single, independent exponential clock e with parameter δ rings, by some specified Lévy process Y without negative jumps reflected below its supremum; IM is the infimum of the path YM, which in turn is defined as Y killed at its last visit of 0 before e; and Y′M is the Vervaat transform of YM. This identity yields an explanation for the geometric distribution of NT (see Kitaev (1993) and Trapman and Bootsma (2009)) and has numerous other applications. In particular, conditional on {NT=n}, and also on {NT=n,T<a}, the ages and residual lifetimes of the n alive individuals at time T are i.i.d. and independent of n. We provide explicit formulae for this distribution and give a more general application to outbreaks of antibiotic-resistant bacteria in the hospital.

Keywords

Branching processsplitting treeCrump–Mode–Jagers processcontour processLévy processscale functionresolventage and residual lifetimeundershoot and overshootVervaat's transformationsamplingdetectionepidemiologyprocessor sharing

MSC classification

Primary: 60J80: Branching processes (Galton-Watson, birth-and-death, etc.)
Secondary: 92D10: Genetics 92D25: Population dynamics (general) 92D30: Epidemiology 92D40: Ecology 60J85: Applications of branching processes 60G17: Sample path properties 60G51: Processes with independent increments; L'evy processes 60G55: Point processes 60K15: Markov renewal processes, semi-Markov processes 60K25: Queueing theory
Type
Research Article
Information
Journal of Applied Probability , Volume 50 , Issue 1 , March 2013 , pp. 208 - 227
Copyright
Copyright © Applied Probability Trust 2013 

References

Bertoin, J. (1996). Lévy Processes. Cambridge University Press.Google Scholar
Bertoin, J. (1997). Exponential decay and ergodicity of completely asymmetric Lévy processes in a finite interval. Ann. Appl. Prob. 7, 156–169.CrossRefGoogle Scholar
Bootsma, M. C. J., Wassenberg, M. W. M., Trapman, P. and Bonten, M. J. M. (2011). The nosocomial transmission rate of animal-associated ST398 meticillin-resistant. J. R. Soc. Interface 8, 578–584.CrossRefGoogle ScholarPubMed
Champagnat, N. and Lambert, A. (2011). Splitting trees with neutral Poissonian mutations II: largest and oldest families. Preprint. Available at http://arxiv.org/abs/1108.4812v1.Google Scholar
Champagnat, N. and Lambert, A. (2012). Splitting trees with neutral Poissonian mutations I: small families. Stoch. Process. Appl. 122, 1003–1033.Google Scholar
Geiger, J. and Kersting, G. (1997). Depth-first search of random trees, and Poisson point processes. In Classical and Modern Branching Processes (Minneapolis, 1994; IMA Math. Appl. Vol. 84), Springer, New York.Google Scholar
Grimmett, G. R. and Stirzaker, D. R. (1992). Probability and Random Processes, 2nd edn. Oxford University Press, New York.Google Scholar
Grishechkin, S. (1992). On a relationship between processor-sharing queues and Crump–Mode–Jagers branching processes. Adv. Appl. Prob. 24, 653–698.Google Scholar
Kallenberg, O. (2002). Foundations of Modern Probability, 2nd edn. Springer, New York.Google Scholar
Kitaev, M. Y. (1993). The M/G/1 processor-sharing model: transient behavior. Queueing Systems 14, 239–273.CrossRefGoogle Scholar
Kyprianou, A. E. (2006). Introductory Lectures on Fluctuations of Lévy Processes with Applications. Springer, Berlin.Google Scholar
Lambert, A. (2009). The allelic partition for coalescent point processes. Markov Process. Relat. Fields 15, 359–386.Google Scholar
Lambert, A. (2010). The contour of splitting trees is a Lévy process. Ann. Prob. 38, 348–395.CrossRefGoogle Scholar
Lambert, A. (2011). Species abundance distributions in neutral models with immigration or mutation and general lifetimes. J. Math. Biol. 63, 57–72.CrossRefGoogle ScholarPubMed
Lambert, A., Simatos, F. and Zwart, B. (2012). Scaling limits via excursion theory: interplay between Crump–Mode–Jagers branching processes and processor-sharing queues. Preprint. Available at http://arxiv.org/abs/1102.5620v2.Google Scholar
Trapman, P. and Bootsma, M. C. J. (2009). A useful relationship between epidemiology and queueing theory: the distribution of the number of infectives at the moment of the first detection. Math. Biosci. 219, 15–22.CrossRefGoogle ScholarPubMed