Clustering and classification of spatio-temporal data using spatial dynamic panel data models

Giuseppe Feo (), Francesco Giordano (), Sara Milito (), Marcella Niglio () and Maria Lucia Parrella ()
Additional contact information
Giuseppe Feo: University of Salerno
Francesco Giordano: University of Salerno
Sara Milito: University of Salerno
Marcella Niglio: University of Salerno
Maria Lucia Parrella: University of Salerno

Advances in Data Analysis and Classification, 2025, vol. 19, issue 2, No 5, 387-435

Abstract: Abstract The class of Spatial Dynamic Panel Data models has been proposed in the socio-econometric literature to analyze spatio-temporal data. In this paper we consider a particular variant of such models, where the set of spatial units is assumed to be partitioned into clusters and the parameters of the model are assumed to be homogeneous within clusters and heterogeneous across clusters. For this model, assuming that the true partition is unknown, we propose a new clustering procedure and a validation test, based on a multiple testing approach, that help to choose the best configuration of model, for a given observed dataset, by estimating the optimal number of clusters and the best partition of units. The validity of the proposed procedures has been shown both theoretically and empirically, on simulated and real data, also compared to alternative methods.

Keywords: Spatial dynamic panel data models; Model selection; Spatial clustering; 62H30; 62H15; 62M30; 91B72; 62J15 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11634-024-00620-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advdac:v:19:y:2025:i:2:d:10.1007_s11634-024-00620-7

Ordering information: This journal article can be ordered from
http://www.springer. ... ds/journal/11634/PS2

DOI: 10.1007/s11634-024-00620-7

Access Statistics for this article

Advances in Data Analysis and Classification is currently edited by H.-H. Bock, W. Gaul, A. Okada, M. Vichi and C. Weihs

More articles in Advances in Data Analysis and Classification from Springer, German Classification Society - Gesellschaft für Klassifikation (GfKl), Japanese Classification Society (JCS), Classification and Data Analysis Group of the Italian Statistical Society (CLADAG), International Federation of Classification Societies (IFCS)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().