The present article offers a certain unifying approach to time series regression modelling by combining partial likelihood (PL) inference and generalized linear models. An advantage gained by resorting to PL is that the joint distribution of the response and the covariates is left unspecified,...

We study the problem of intervention effects generating various types of outliers in a linear count time-series model. This model belongs to the class of observation-driven models and extends the class of Gaussian linear time-series models within the exponential family framework. Studies about...

We consider nonparametric estimation and testing of linearity in a panel of intercorrelated time series. We place the emphasis on the situation where there are many time series in the panel but few observations for each of the series. The intercorrelation is described by a latent process, and a...