Exponential ergodicity of branching processes with immigration and competition

Pei Sen Li, Zenghu Li, Jian Wang, Xiaowen Zhou

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We study the ergodic property of a continuous-state branching process with immigration and competition. The exponential ergodicity in a weighted total variation distance is proved under natural assumptions. The main theorem applies to subcritical, critical and supercritical branching mechanisms, including all those of stable types. The proof is based on the construction of a Markov coupling process and the choice of a nonsymmetric control function for the distance. Those are designed to identify and to take the advantage of the dominating factor from the branching, immigration and competition mechanisms in different parts of the state space. The approach provides a way of finding a lower bound of the ergodicity rate.

Original languageEnglish
Pages (from-to)350-384
Number of pages35
JournalAnnales de l'institut Henri Poincare (B) Probability and Statistics
Volume61
Issue number1
DOIs
Publication statusPublished - Feb 2025

Keywords

  • Competition
  • Continuous-state branching process
  • Control function
  • Exponential ergodicity
  • Immigration
  • Markov coupling
  • Stochastic equation

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