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Random coefficients bifurcating autoregressive processes

Benoîte de SaportaAnne Gégout-PetitLaurence Marsalle — 2014

ESAIM: Probability and Statistics

This paper presents a new model of asymmetric bifurcating autoregressive process with random coefficients. We couple this model with a Galton−Watson tree to take into account possibly missing observations. We propose least-squares estimators for the various parameters of the model and prove their consistency, with a convergence rate, and asymptotic normality. We use both the bifurcating Markov chain and martingale approaches and derive new results in both these frameworks.

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