Generalized spatio-temporal models
An important problem in statistics is the study of spatio-te mporal data taking into account the effect of explanatory variables such as latitude, longitud e and time. In this paper, a new Bayesian approach for analyzing spatial longitudinal data is propos ed. It takes into account linear time regre...
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/13275 |
| Acceso en línea: | https://hdl.handle.net/2099/13275 |
| Access Level: | acceso abierto |
| Palabra clave: | Mathematical statistics fisher scoring mean-covariance modelling antedependence spatial statistics spatial temporal models, spatial longitudinal data Bayesian Estadística matemàtica Classificació AMS::62 Statistics::62F Parametric inference Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
| Sumario: | An important problem in statistics is the study of spatio-te mporal data taking into account the effect of explanatory variables such as latitude, longitud e and time. In this paper, a new Bayesian approach for analyzing spatial longitudinal data is propos ed. It takes into account linear time regression structures on the mean and linear regression str uctures on the variance-covariance matrix of normal observations. The spatial structure is inc luded in the time regression parameters and also in the regression structure of the variance covaria nce matrix. Initially, we present a summary of the spatial models and the Bayesian methodology u sed to fit the models, as a extension of the longitudinal data analysis. Next, the gene ral spatial temporal model is proposed. Finally, this proposal is used to study rainfall data |
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