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Uncertainty under a multivariate nested-error regression model with logarithmic transformation

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorMolina, Isabeles
dc.date.accessioned2006-11-15T16:02:03Z
dc.date.available2006-11-15T16:02:03Z
dc.date.issued2006-10es
dc.description.abstractAssuming a multivariate linear regression model with one random factor, we consider the parameters defined as exponentials of mixed effects, i.e., linear combinations of fixed and random effects. Such parameters are of particular interest in prediction problems where the dependent variable is the logarithm of the variable that is the object of inference. We derive bias-corrected empirical predictors of such parameters. A second order approximation for the mean crossed product error of the predictors of two of these parameters is obtained, and an estimator is derived from it. The mean squared error is obtained as a particular case.es
dc.format.extent255936 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.repecws066117
dc.identifier.urihttps://hdl.handle.net/10016/443
dc.language.isoenges
dc.language.isoenges
dc.relation.ispartofseriesUC3M Working Papers. Statistics and Econometricses
dc.relation.ispartofseries2006-17es
dc.rights.accessRightsopen access
dc.subject.ecienciaEstadística
dc.titleUncertainty under a multivariate nested-error regression model with logarithmic transformationes
dc.typeworking paper*
dspace.entity.typePublication
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