6533b7d5fe1ef96bd126448a

RESEARCH PRODUCT

CENTRAL LIMIT THEOREM FOR KERNEL ESTIMATOR OF INVARIANT DENSITY IN BIFURCATING MARKOV CHAINS MODELS

Siméon Valère Bitseki PendaJean-françois Delmas

subject

[MATH.MATH-PR]Mathematics [math]/Probability [math.PR][MATH.MATH-PR] Mathematics [math]/Probability [math.PR]fluctuations for tree indexed Markov chain60J8060J05[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Bifurcating Markov chains60F05binary trees[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]bifurcating auto-regressive process62F12density estimation Mathematics Subject Classification (2020): 62G05

description

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. Motivated by the functional estimation of the density of the invariant probability measure which appears as the asymptotic distribution of the trait, we prove the consistence and the Gaussian fluctuations for a kernel estimator of this density based on late generations. In this setting, it is interesting to note that the distinction of the three regimes on the ergodic rate identified in a previous work (for fluctuations of average over large generations) disappears. This result is a first step to go beyond the threshold condition on the ergodic rate given in previous statistical papers on functional estimation.

https://hal.archives-ouvertes.fr/hal-03261877/document