This paper is concerned with an observation driven model for time series of counts whose conditional distribution given past observations follows a Poisson distribution. This class of models, called GLARMA, is capable of modeling a wide range of dependence structures and is readily estimated using conditional maximum likelihood. Recursive formulae for carrying out maximum likelihood estimation ...

We study nonparametric maximum likelihood estimation of a log–concave probability density and its distribution and hazard function. Some general properties of these estimators are derived from two characterizations. It is shown that the rate of convergence with respect to supremum norm on a compact interval for the density and hazard rate estimator is at least (log(n)/n) and typically (log(n)/n...