dc.creatorVelandia Munoz, Daira Luz
dc.creatorBachoc, François
dc.creatorBevilacqua, Moreno
dc.creatorGendre, Xavier
dc.creatorLoubes, Jean Michel
dc.date2018-11-26T19:07:58Z
dc.date2018-11-26T19:07:58Z
dc.date2017
dc.date.accessioned2023-10-03T20:07:12Z
dc.date.available2023-10-03T20:07:12Z
dc.identifier19357524
dc.identifierhttp://hdl.handle.net/11323/1878
dc.identifierhttps://doi.org/10.1214/17-EJS1298
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9174356
dc.descriptionWe consider maximum likelihood estimation with data from a bivariate Gaussian process with a separable exponential covariance model under fixed domain asymptotics. We first characterize the equivalence of Gaussian measures under this model. Then consistency and asymptotic normality for the maximum likelihood estimator of the microergodic parameters are established. A simulation study is presented in order to compare the finite sample behavior of the maximum likelihood estimator with the given asymptotic distribution.
dc.formatapplication/pdf
dc.languageeng
dc.publisherElectronic Journal of Statistics
dc.rightsAtribución – No comercial – Compartir igual
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectBivariate exponential model
dc.subjectEquivalent Gaussian measures
dc.subjectInfill asymptotics
dc.subjectMicroergodic parameters
dc.titleMaximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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