Density estimation for spatial-temporal models

dc.creatorForzani, Liliana Maria
dc.creatorFraiman, Ricardo
dc.creatorLlop Orzan, Pamela Nerina
dc.date.accessioned2017-08-03T21:33:35Z
dc.date.accessioned2018-11-06T11:24:38Z
dc.date.available2017-08-03T21:33:35Z
dc.date.available2018-11-06T11:24:38Z
dc.date.created2017-08-03T21:33:35Z
dc.date.issued2012-12
dc.identifierForzani, Liliana Maria; Fraiman, Ricardo; Llop Orzan, Pamela Nerina; Density estimation for spatial-temporal models; Springer; Test; 22; 2; 12-2012; 321-342
dc.identifier1133-0686
dc.identifierhttp://hdl.handle.net/11336/21847
dc.identifier1863-8260
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1850972
dc.description.abstractIn this paper a k-nearest neighbor type estimator of the marginal density function for a random field which evolves with time is considered. Considering dependence, the consistency and asymptotic distribution are studied for the stationary and nonstationary cases. In particular, the parametric rate of convergence √T is proven when the random field is stationary. The performance of the estimator is shown by applying our procedure to a real data example.
dc.languageeng
dc.publisherSpringer
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007%2Fs11749-012-0313-3
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1007/s11749-012-0313-3
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectDensity estimation
dc.subjectLocal times
dc.subjectspatio-temporal data
dc.titleDensity estimation for spatial-temporal models
dc.typeArtículos de revistas
dc.typeArtículos de revistas
dc.typeArtículos de revistas


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