Visualizing And Exploring Multiple Time Series
Giuseppe Giordano, Cristina Davino, Piazza Oberdan · U-PAD Unimc - Open Digital Publications (University of Macerata) · 2005
Aim of this paper is to present a way to explore time series by combining some fundamental results of stochastic processes theory with graphical and reduction features of factorial methods. A multiple time series visualization and identification strategy is provided by defining a common structural subspace where different regions related to particular ARMA processes are represented. This subspace becomes the reference map for the exploration of multiple time series. In order to provide a unique identification of the ARMA model, a complementary tool represented by a classification tree is proposed.