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Automatic spectral density estimation for Random fields on a lattice via bootstrap

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dc.affiliation.dptoUC3M. Departamento de Economía de la Empresaes
dc.contributor.authorVidal-Sanz, Jose M.
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Economía de la Empresa
dc.date.accessioned2007-04-02T10:58:28Z
dc.date.accessioned2009-04-01T11:01:21Z
dc.date.available2007-04-02T10:58:28Z
dc.date.available2009-04-01T11:01:21Z
dc.date.issued2007-05
dc.descriptionCorrected version in March 2009
dc.description.abstractThis paper considers the nonparametric estimation of spectral densities for second order stationary random fields on a d-dimensional lattice. I discuss some drawbacks of standard methods, and propose modified estimator classes with improved bias convergence rate, emphasizing the use of kernel methods and the choice of an optimal smoothing number. I prove uniform consistency and study the uniform asymptotic distribution, when the optimal smoothing number is estimated from the sampled data.
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dc.identifier.repecwb072606
dc.identifier.urihttps://hdl.handle.net/10016/680
dc.language.isoeng
dc.language.isoeng
dc.relation.hasversionhttp://hdl.handle.net/10016/7344
dc.relation.ispartofseriesUC3M Working papers. Business Economics
dc.relation.ispartofseries07-06
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEmpresa
dc.subject.otherSpatial data
dc.subject.otherSpectral density
dc.subject.otherSmoothing number
dc.subject.otherUniform asymptotic distribution
dc.subject.otherBootstrap
dc.titleAutomatic spectral density estimation for Random fields on a lattice via bootstrap
dc.typeworking paper*
dspace.entity.typePublication
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