Central limit theorem for bifurcating markov chains under L2-ergodic conditions

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Abstract

Bifurcating Markov chains (BMCs) 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 additive functionals of BMCs under -ergodic conditions with three different regimes. This completes the pointwise approach developed in a previous work. As an application, we study the elementary case of a symmetric bifurcating autoregressive process, which justifies the nontrivial hypothesis considered on the kernel transition of the BMCs. We illustrate in this example the phase transition observed in the fluctuations.

Original languageEnglish
Pages (from-to)999-1031
Number of pages33
JournalAdvances in Applied Probability
Volume54
Issue number4
DOIs
Publication statusPublished - 15 Dec 2022

Keywords

  • Bifurcating Markov chains
  • bifurcating autoregressive process
  • binary trees
  • density estimation
  • fluctuations for tree-indexed Markov chains

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