Lookup NU author(s): Professor Emilio Porcu
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© 2018 Elsevier B.V. Simultaneous autoregressive (SAR) models have been extensively used for the analysis of spatial data in areas as diverse as demography, economy and geography. These are linear models with a scalar response, scalar explanatory variables and autoregressive errors. In this work we extend this modeling approach from scalar to functional covariates. Least squares and maximum likelihood are used as estimation methods of the parameters. A simulation study is considered for evaluating the performance of the proposed methodology. As an illustration, the model is used to establish the relationship between unsatisfied basic needs and curves of gross domestic product obtained in 32 departments of Colombia (districts of the country).
Author(s): Pineda-Rios W, Giraldo R, Porcu E
Publication type: Article
Publication status: Published
Journal: Spatial Statistics
Print publication date: 01/03/2019
Online publication date: 19/12/2018
Acceptance date: 11/12/2018
ISSN (print): 2211-6753
Publisher: Elsevier B.V.
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