  This paper presents a 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 their asymptotic normality. We use both the
bifurcating Markov chain and martingale approaches and derive new important
general results in both these frameworks.
