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Nonparametric tilted density function estimation: A cross-validation criterion
dc.contributor.author | Doosti, Hassan | |
dc.contributor.author | Hall, Peter | |
dc.contributor.author | Mateu, Jorge | |
dc.date.accessioned | 2018-07-25T07:40:00Z | |
dc.date.available | 2018-07-25T07:40:00Z | |
dc.date.issued | 2018-12 | |
dc.identifier.citation | DOOSTI, Hassan; HALL, Peter; MATEU, Jorge. Nonparametric tilted density function estimation: A cross-validation criterion. Journal of Statistical Planning and Inference, 2018, vol. 197, p. 51-68. | ca_CA |
dc.identifier.uri | http://hdl.handle.net/10234/175786 | |
dc.description.abstract | In this paper, we propose a tilted estimator for nonparametric estimation of a density function. We use a cross-validation criterion to choose both the bandwidth and the tilted estimator parameters. We demonstrate theoretically that our proposed estimator provides a convergence rate which is strictly faster than the usual rate attained using a conventional kernel estimator with a positive kernel. We investigate the performance through both theoretical and numerical studies. | ca_CA |
dc.format.extent | 17 p. | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.rights | © 2018 Elsevier B.V. All rights reserved. | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | cross validation function | ca_CA |
dc.subject | non-parametric density function estimation | ca_CA |
dc.subject | rate of convergence | ca_CA |
dc.subject | tilted estimators | ca_CA |
dc.title | Nonparametric tilted density function estimation: A cross-validation criterion | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1016/j.jspi.2017.12.003 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://www.sciencedirect.com/science/article/pii/S037837581730215X | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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