Parsimonious periodic autoregressive models for time series with evolving trend and seasonality
This paper proposes an extension of Periodic AutoRegressive (PAR) modelling for time series with evolving features. The
large scale of modern datasets, in fact, implies that the time span may subtend several evolving patterns of the underlying
series, affecting also seasonality. The proposed model allows several regimes in time and a possibly different PAR process
with a trend term in each regime. The means, autocorrelations and residual variances may change both with the regime and