Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98061
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dc.contributor.authorLian, Hengen
dc.date.accessioned2013-08-29T07:49:42Zen
dc.date.accessioned2019-12-06T19:50:11Z-
dc.date.available2013-08-29T07:49:42Zen
dc.date.available2019-12-06T19:50:11Z-
dc.date.copyright2012en
dc.date.issued2012en
dc.identifier.citationLian, H. (2012). Convergence of nonparametric functional regression estimates with functional responses. Electronic Journal of Statistics, 6(0), 1373-1391.en
dc.identifier.issn1935-7524en
dc.identifier.urihttps://hdl.handle.net/10356/98061-
dc.description.abstractWe consider nonparametric functional regression when both predictors and responses are functions. More specifically, we let (X 1 ,Y 1 ),…,(X n ,Y n ) be random elements in F×H where F is a semi-metric space and H is a separable Hilbert space. Based on a recently introduced notion of weak dependence for functional data, we showed the almost sure convergence rates of both the Nadaraya-Watson estimator and the nearest neighbor estimator, in a unified manner. Several factors, including functional nature of the responses, the assumptions on the functional variables using the Orlicz norm and the desired generality on weakly dependent data, make the theoretical investigations more challenging and interesting.en
dc.language.isoenen
dc.relation.ispartofseriesElectronic journal of statisticsen
dc.titleConvergence of nonparametric functional regression estimates with functional responsesen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen
dc.identifier.doi10.1214/12-EJS716en
item.fulltextNo Fulltext-
item.grantfulltextnone-
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