Clustering space-time series: FSTAR as a flexible STAR approach

Edoardo Otranto and Massimo Mucciardi ()
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Massimo Mucciardi: University of Messina

Advances in Data Analysis and Classification, 2019, vol. 13, issue 1, No 8, 175-199

Abstract: 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.

Keywords: Clustering; Forecasting; Space–time models; Spatial weight matrix; 62M10; 91B72; 91C20 (search for similar items in EconPapers)
JEL-codes: C30 C38 C50 J11 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11634-018-0314-5

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