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dc.contributor.advisorBevilacqua, Moreno
dc.creatorCaamaño-Carrillo, Christian Eloy
dc.date.accessioned2018-06-18T13:08:40Z
dc.date.available2018-06-18T13:08:40Z
dc.date.issued2018es_CL
dc.identifier.urihttp://hdl.handle.net/10533/214737
dc.description.abstractIn this work, we propose two types of models for the analysis of regression and dependence of positive and continuous spatio-temporal data, and of continuous spatio-temporal data with possible asymmetry and/or heavy tails. For the first case, we propose two (possibly non stationary) random fields with Gamma and Weibull marginals. Both random fields are obtained transforming a rescaled sum of independent copies of squared Gaussian random fields. For the second case, we propose a random field with t marginal distribution. We then consider two possible generalizations allowing for possible asymmetry. In the first approach we obtain a skew-t random field mixing a skew Gaussian random field with an inverse square root Gamma random field. In the second approach we obtain a two piece t random field mixing a specific binary discrete random field with half-t random field. We study the associated second order properties and in the stationary case, the geometrical properties. Since maximum likelihood estimation is computationally unfeasible, even for relatively small data-set, we propose the use of the pairwise likelihood. The effectiveness of our proposal for the gamma and weibull cases, is illustrated through a simulation study and a re-analysis of the Irish Wind speed data (Haslett and Raftery, 1989) without considering any prior transformation of the data as in previous statistical analysis. For the t and asymmetric t cases we present a simulated study in order to show the performance of our method.es_CL
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.rightsinfo:eu-repo/semantics/openAccesses_CL
dc.titleModeling and estimation of some non Gaussian random fieldses_CL
dc.titleModeling and estimatión of some non gaussian random fields
dc.contributor.institutionUNIVERSIDAD DE VALPARAISOes_CL
dc.identifier.folio21150156es_CL
dc.country.isoChilees_CL
dc.relation.projectidinfo:eu-repo/grantAgreement//21150156es_CL
dc.relation.setinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93488
dc.rights.driverinfo:eu-repo/semantics/openAccess
dc.type.driverinfo:eu-repo/semantics/doctoralThesises_CL
dc.type.tesisTesis
dc.subject.oecd1nIngeniería y Tecnologíaes_CL
dc.subject.oecd2nOtras Ingenierías y Tecnologíases_CL
dc.subject.oecd3nOtras Ingenierías y Tecnologíases_CL
dc.type.openaireinfo:eu-repo/semantics/publishedVersion


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