CENTRAL LIMIT THEOREM FOR BIFURCATING MARKOV CHAINS UNDER POINTWISE ERGODIC CONDITIONS

S. Valère Bitseki Penda, Jean François Delmas

Research output: Contribution to journalArticlepeer-review

Abstract

Bifurcating Markov chains (BMC) are Markov chains indexed by a full binary tree representing the evolution of a trait along a population where each individual has two children. We provide a central limit theorem for general additive functionals of BMC, and prove the existence of three regimes. This corresponds to a competition between the reproducing rate (each individual has two children) and the ergodicity rate for the evolution of the trait. This is in contrast with the work of Guyon (Ann. Appl. Probab. 17 (2007) 1538–1569), where the considered additive functionals are sums of martingale increments, and only one regime appears. Our result can be seen as a discrete time version, but with general trait evolution, of results in the time continuous setting of branching particle system from Adamczak and Miłos´ (Electron. J. Probab. 20 (2015) 42), where the evolution of the trait is given by an Ornstein–Uhlenbeck process.

Original languageEnglish
Pages (from-to)3817-3849
Number of pages33
JournalAnnals of Applied Probability
Volume32
Issue number5
DOIs
Publication statusPublished - 1 Oct 2022

Keywords

  • Bifurcating Markov chains
  • binary trees
  • central limit theorem
  • tree indexed Markov chain

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