Generalized spatio-temporal models

• Autores: Edilberto Cepeda Cuervo
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 35, Nº. 2, 2011, págs. 165-178
• Idioma: inglés
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• Dialnet Métricas: 1 Cita
• Resumen

  • An important problem in statistics is the study of spatio-temporal data taking into account the effect of explanatory variables such as latitude, longitude and time. In this paper, a new Bayesian approach for analyzing spatial longitudinal data is proposed. It takes into account linear time regression structures on the mean and linear regression structures on the variance-covariance matrix of normal observations. The spatial structure is included in the time regression parameters and also in the regression structure of the variance covariance matrix. Initially, we present a summary of the spatial models and the Bayesian methodology used to fit the models, as a extension of the longitudinal data analysis. Next, the general spatial temporal model is proposed.

    Finally, this proposal is used to study rainfall data.

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