In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local...

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested...

The purpose of this paper is to study the identification methods of the nature of the seasonal component of a time series. These methods are represented by the verifying tests of the unit root for the models of seasonal autoregressive processes: the HEGY test, the Franses test, etc. In practice,...