Functional SAR models: with application to spatial econometrics

dc.contributor.authorPineda-Ríos, Wilmerspa
dc.contributor.authorGiraldo, Ramónspa
dc.contributor.authorPorcu, Emiliospa
dc.coverage.campusCRAI-USTA Bogotáspa
dc.date.accessioned2019-06-18T22:07:06Zspa
dc.date.available2019-06-18T22:07:06Zspa
dc.date.issued2018-12-19spa
dc.description.abstractSimultaneous 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).spa
dc.description.domainhttp://unidadinvestigacion.usta.edu.cospa
dc.format.mimetypeapplication/pdfspa
dc.identifier.citationPineda-Ríos, W., Giraldo, R., & Porcu, E. (2018). Functional SAR models: With application to spatial econometrics. Bogotá: doi:10.1016/j.spasta.2018.12.002spa
dc.identifier.doihttps://doi.org/10.1016/j.spasta.2018.12.002spa
dc.identifier.urihttp://hdl.handle.net/11634/17176
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dc.rightsAtribución-NoComercial-CompartirIgual 2.5 Colombia*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/2.5/co/*
dc.subject.keywordAutoregressive errorsspa
dc.subject.keywordFunctional linear modelsspa
dc.subject.keywordSpatial dependencespa
dc.subject.keywordSpatial weight matrixspa
dc.titleFunctional SAR models: with application to spatial econometricsspa
dc.type.categoryGeneración de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicosspa

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