The occurrence of influenza epidemics during winters, in the northern hemisphere countries, is known to be associated with observed excess mortality for all causes. A large variety of methods have been developed in order to estimate, from weekly or monthly mortality time series, the number of influenza-associated deaths in each season. The present work focus on the group of methods characterised by fitting statistical models to interrupted mortality time series. The study objective is to find a common ground between these methods in order to describe and compare them. They are unified in a single class, being categorised according to three main parameters: the model used to fit the interrupted time series and obtain a baseline, the a priori chosen type of periods used to estimate the influenza epidemic periods and the procedure used to fit the model to the time series (iterative or non-iterative). This generalisation led quite naturally to the construction of a set of user friendly R-routines, package flubase, implementing all these models. These routines were applied to data on about 20 years of weekly Portuguese number of deaths by pneumonia and influenza showing that, in this case, the parameter that had the highest impact on influenza-associated deaths estimates was the a priori chosen type of period used.