3 citations · 3 across the 3 of their papers we have counts for
4 papers
General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator
Tepmony Sim, Randal Douc, François Roueff
The class of observation-driven models (ODMs) includes many models of non-linear time series which, in a fashion similar to, yet different from, hidden Markov models (HMMs), involv…
Necessary and sufficient conditions for the identifiability of observation-driven models
François Roueff, Randal Douc, Ois Roueff +1
In this contribution we are interested in proving that a given observation-driven model is identifiable. In the case of a GARCH(p, q) model, a simple sufficient condition has been…
The maximizing set of the asymptotic normalized log-likelihood for partially observed Markov chains
Randal Douc, Francois Roueff, Tepmony Sim
This paper deals with a parametrized family of partially observed bivariate Markov chains. We establish that, under very mild assumptions, the limit of the normalized log-likelihoo…
Handy sufficient conditions for the convergence of the maximum likelihood estimator in observation-driven models
Randal Douc, François Roueff, Tepmony Sim
This paper generalizes asymptotic properties obtained in the observation-driven times series models considered by \cite{dou:kou:mou:2013} in the sense that the conditional law of e…