Many-to-few for non-local branching Markov process
POWELL, Ellen
Department of Mathematical Sciences [Durham University]
Méthodes avancées d’apprentissage statistique et de contrôle [ASTRAL]
< Réduire
Department of Mathematical Sciences [Durham University]
Méthodes avancées d’apprentissage statistique et de contrôle [ASTRAL]
Langue
en
Document de travail - Pré-publication
Résumé en anglais
We provide a many-to-few formula in the general setting of non-local branching Markov processes. This formula allows one to compute expectations of k-fold sums over functions of the population at k different times. The ...Lire la suite >
We provide a many-to-few formula in the general setting of non-local branching Markov processes. This formula allows one to compute expectations of k-fold sums over functions of the population at k different times. The result generalises [14] to the non-local setting, as introduced in [11] and [8]. As an application, we consider the case when the branching process is critical, and conditioned to survive for a large time. In this setting, we prove a general formula for the limiting law of the death time of the most recent common ancestor of two particles selected uniformly from the population at two different times, as t → ∞. Moreover, we describe the limiting law of the population sizes at two different times, in the same asymptotic regime.< Réduire
Mots clés en anglais
non-local branching processes
many-to-few
spines
Origine
Importé de halUnités de recherche