On conditioning a self-similar growth-fragmentation by its intrinsic area

被引:3
作者
Bertoin, Jean [1 ]
Curien, Nicolas [2 ,3 ]
Kortchemski, Igor [4 ,5 ]
机构
[1] Univ Zurich, Inst Math, Zurich, Switzerland
[2] Univ Paris Sud, Dept Math, Paris, France
[3] Inst Univ France, Paris, France
[4] Ecole Polytech, CNRS, Palaiseau, France
[5] Ecole Polytech, CMAP, Palaiseau, France
来源
ANNALES DE L INSTITUT HENRI POINCARE-PROBABILITES ET STATISTIQUES | 2021年 / 57卷 / 02期
关键词
Growth-fragmentation; Branching process; Self-similarity; Smoothing transform; Intrinsic martingale; SIMILAR MARKOV-PROCESSES; CONTINUITY; LAWS;
D O I
10.1214/20-AIHP1110
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The genealogical structure of self-similar growth-fragmentations can be described in terms of a branching random walk. The so-called intrinsic area A arises in this setting as the terminal value of a remarkable additive martingale. Motivated by connections with some models of random planar geometry, the purpose of this work is to investigate the effect of conditioning a self-similar growth-fragmentation on its intrinsic area. The distribution of A is a fixed point of a useful smoothing transform which enables us to establish the existence of a regular density a and to determine the asymptotic behavior of a(r) as r -> infinity (this can be seen as a local version of Kesten-Grincevi.cius-Goldie theorem's for random affine fixed point equations in a particular setting). In turn, this yields a family of martingales from which the formal conditioning on A = r can be realized by probability tilting. We point at a limit theorem for the conditional distribution given A = r as r -> infinity, and also observe that such conditioning still makes sense under the so-called canonical measure for which the growth-fragmentation starts from 0.
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页码:1136 / 1156
页数:21
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