The general purpose of this textbook is to provide analysts in statistical institutes with
a unied view of applied analysis of time series as can be conducted in the framework
of linear stochastic models of the Arima-type. The issues discussed are modelling
and forecasting, ltering, signal extraction and Unobserved Components analysis, and
regression in time series models. The main concern is to help the readers in understanding some important tools that progress in statistical theory has made available. Emphasis is thus put on practical aspects, and the readers will nd implementations
of the techniques described in softwares like Seats-Tramo (see Gomez and Maravall,
1996) and X12-Arima (see Findley and al., 1996).