dc.creator | Rivas Martínez, Gustavo Ignacio | es |
dc.creator | Jiménez Gamero, María Dolores | es |
dc.date.accessioned | 2018-03-05T07:13:27Z | |
dc.date.available | 2018-03-05T07:13:27Z | |
dc.date.issued | 2018-01 | |
dc.identifier.citation | Rivas Martínez, G.I. y Jiménez Gamero, M.D. (2018). Computationally efficient goodness-of-fit tests for the error distribution in nonparametric regression. Revstat Statistical Journal, 16 (1), 137-166. | |
dc.identifier.issn | 1645-6726 | es |
dc.identifier.uri | https://hdl.handle.net/11441/70740 | |
dc.description.abstract | Several procedures have been proposed for testing goodness-of-fit to the error distribution in nonparametric regression models. The null distribution of the associated test statistics is usually approximated by means of a parametric bootstrap which, under certain conditions, provides a consistent estimator. This paper considers a goodness-of-fit test whose test statistic is an L2 norm of the difference between the empirical characteristic function of the residuals and a parametric estimate of the characteristic function in the null hypothesis. It is proposed to approximate the null distribution through a weighted bootstrap which also produces a consistent estimator of the null distribution but, from a computational point of view, is more efficient than
the parametric bootstrap. | es |
dc.description.sponsorship | Fundación Carolina | es |
dc.description.sponsorship | Universidad Nacional de Asunción | es |
dc.description.sponsorship | Universidad de Sevilla | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Instituto Nacional de Estatística (Portugal) | es |
dc.relation.ispartof | Revstat Statistical Journal, 16 (1), 137-166. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Goodness-of-fit | es |
dc.subject | Empirical characteristic function | es |
dc.subject | Regression residuals | es |
dc.subject | Weighted bootstrap | es |
dc.subject | Consistency | es |
dc.title | Computationally efficient goodness-of-fit tests for the error distribution in nonparametric regression | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa | es |
dc.relation.projectID | MTM2014-55966-P | es |
dc.relation.projectID | MTM2017-89422-P | es |
dc.relation.publisherversion | https://www.ine.pt/revstat/pdf/REVSTAT_v16-n1-7.pdf | es |
dc.contributor.group | Universidad de Sevilla. FQM153: Estadística e Investigación Operativa | es |
idus.format.extent | 30 p. | es |
dc.journaltitle | Revstat Statistical Journal | es |
dc.publication.volumen | 16 | es |
dc.publication.issue | 1 | es |
dc.publication.initialPage | 137 | es |
dc.publication.endPage | 166 | es |