The STAR model is widely used to represent the dynamics of a certain variable recorded at several locations at the same time. Its advantages are often discussed in terms of parsimony with respect to space-time VAR structures because it considers a single coefficient for each time and spatial lag. This hypothesis can be very strong; we add a certain degree of flexibility to the STAR model, providing the possibility for coefficients to vary in groups of locations. The new class of models (called Flexible STAR–FSTAR) is compared to the classical STAR and the space-time VAR by simulations and an application.
Clustering space-time series: FSTAR as a flexible STAR approach / Otranto, Edoardo; Mucciardi, Massimo. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 13:1(2019), pp. 175-199. [10.1007/s11634-018-0314-5]
Clustering space-time series: FSTAR as a flexible STAR approach
Edoardo Otranto;
2019
Abstract
The STAR model is widely used to represent the dynamics of a certain variable recorded at several locations at the same time. Its advantages are often discussed in terms of parsimony with respect to space-time VAR structures because it considers a single coefficient for each time and spatial lag. This hypothesis can be very strong; we add a certain degree of flexibility to the STAR model, providing the possibility for coefficients to vary in groups of locations. The new class of models (called Flexible STAR–FSTAR) is compared to the classical STAR and the space-time VAR by simulations and an application.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
