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dc.rights.licenseAtribución-NoComercial 4.0 Internacional
dc.contributor.authorCepeda-Cuervo, Edilberto
dc.contributor.authorAndrade, Marinho G.
dc.contributor.authorAchcar, Jorge Alberto
dc.description.abstractTime series models are often used in the analysis of Meteorological phenomena to model levels of rainfall, temperature and levels of air humidity series in order to make forecasting and generate synthetic series which are inputs for the analysis of the influence of these variables on the quality of life. Relative air humidity for example, has great influence on the count increasing of respiratory diseases, especially for some age populations as newly born and elderly people. In this paper we introduce a new modeling approach for meteorological time series assuming a beta distribution for the data, where both the mean and precision parameters are being modeled. Bayesian methods using standard MCMC (Markov Chain Monte Carlo Methods) are used to simulate samples for the joint posterior distribution of interest. An example is given with a time series of 313 air humidity observations, measured by a wether station of Rio Claro, a city localized in S˜ao Paulo state, southeastern of Brazil.
dc.relation.ispartofUniversidad Nacional de Colombia Sede Bogotá Facultad de Ciencias Departamento de Estadística
dc.relation.ispartofDepartamento de Estadística
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.subject.ddc5 Ciencias naturales y matemáticas / Science
dc.subject.ddc55 Ciencias de la tierra / Earth sciences and geology
dc.titleBeta meteorological time series: application to air humidity data
dc.typeDocumento de trabajo
dc.relation.referencesCepeda-Cuervo, Edilberto and Andrade, Marinho G. and Achcar, Jorge Alberto Beta meteorological time series: application to air humidity data. Reporte técnico. Sin Definir. (No publicado)
dc.subject.proposalMeteorological time series data
dc.subject.proposalbeta distribution
dc.subject.proposalBayesian analysis, MCMC methods
dc.subject.proposalMCMC methods

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Atribución-NoComercial 4.0 InternacionalThis work is licensed under a Creative Commons Reconocimiento-NoComercial 4.0.This document has been deposited by the author (s) under the following certificate of deposit