Abstract
We consider a system of independent branching random walks on R which start from a Poisson point process with intensity of the form eλ(du) = e-λudu, where λ ∈ R is chosen in such a way that the overall intensity of particles is preserved. Denote by χ the cluster distribution, and let φ be the log-Laplace transform of the intensity of χ. If λφ'(λ) > 0, we show that the system is persistent, meaning that the point process formed by the particles in the nth generation converges as n → ∞ to a non-trivial point process Πeλχ with intensity eλ. If λφ'(λ) < 0 then the branching population suffers local extinction, meaning that the limiting point process is empty. We characterize point processes on R which are cluster invariant with respect to the cluster distribution χ as mixtures of the point processes Πceλχ over c > 0 and λ ∈ Kst, where Kst = {λ ∈ R: φ(λ) = 0, λφ'(λ) > 0}.
Publisher
Cambridge University Press (CUP)
Subject
Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability
Reference24 articles.
1. [20] Maillard P. (2011). A characterisation of superposable random measures. Preprint. Available at http://arxiv.org/{}abs/1102.1888v1.
2. [19] Madaule T. (2011). Convergence in law for the branching random walk seen from its tip. Preprint. Available at http://arxiv.org/abs/arXiv:1107.2543v2.
3. Conceptual Proofs of $L$ Log $L$ Criteria for Mean Behavior of Branching Processes
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The fixed points of branching Brownian motion;Probability Theory and Related Fields;2022-12-29