Nonparametric Bayesian Modeling and Estimation of Spatial Correlation Functions for Global Data

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dc.contributor.authorPorcu, Emilio
dc.contributor.authorBissiri, Pier Giovanni
dc.contributor.authorTagle, Felipe
dc.contributor.authorSoza, Ruben
dc.contributor.authorQuintana, Fernando A.
dc.date.accessioned2024-01-10T13:45:01Z
dc.date.available2024-01-10T13:45:01Z
dc.date.issued2021
dc.description.abstractWe provide a nonparametric spectral approach to the modeling of correlation functions on spheres. The sequence of Schoenberg coefficients and their associated covariance functions are treated as random rather than assuming a parametric form. We propose a stick-breaking representation for the spectrum, and show that such a choice spans the support of the class of geodesically isotropic covariance functions under uniform convergence. Further, we examine the first order properties of such representation, from which geometric properties can be inferred, in terms of Ho spacing diaeresis lder continuity, of the associated Gaussian random field. The properties of the posterior, in terms of existence, uniqueness, and Lipschitz continuity, are then inspected. Our findings are validated with MCMC simulations and illustrated using a global data set on surface temperatures.
dc.description.funderChilean Commission for Scientific and Technological Research
dc.description.funderIniciativa Cientifica Milenio -Minecon Nucleo Milenio MIDAS
dc.fechaingreso.objetodigital2024-05-15
dc.format.extent29 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1214/20-BA1228
dc.identifier.eissn1936-0975
dc.identifier.issn1931-6690
dc.identifier.urihttps://doi.org/10.1214/20-BA1228
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/78971
dc.identifier.wosidWOS:000690470400006
dc.information.autorucFacultad de Matemáticas; Quintana Quintana, Fernando Andres; S/I; 100343
dc.issue.numero3
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final873
dc.pagina.inicio845
dc.publisherINT SOC BAYESIAN ANALYSIS
dc.revistaBAYESIAN ANALYSIS
dc.rightsacceso abierto
dc.subjectcorrelation function
dc.subjectgreat-circle distance
dc.subjectmean square differentiability
dc.subjectnonparametric Bayes
dc.subjectspheres
dc.subjectCOVARIANCE FUNCTIONS
dc.subjectRANDOM-FIELDS
dc.subjectINFERENCE
dc.subjectDIMENSION
dc.subjectDISTANCE
dc.subject.ods02 Zero Hunger
dc.subject.odspa02 Hambre cero
dc.titleNonparametric Bayesian Modeling and Estimation of Spatial Correlation Functions for Global Data
dc.typeartículo
dc.volumen16
sipa.codpersvinculados100343
sipa.indexWOS
sipa.trazabilidadCarga SIPA;09-01-2024
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