dc.contributor.author | Politis, Dimitris Nicolas | en |
dc.contributor.editor | Politis, Dimitris Nicolas | en |
dc.contributor.editor | Akritas, Michael G. | en |
dc.contributor.editor | Lahiri S.N. | en |
dc.creator | Politis, Dimitris Nicolas | en |
dc.date.accessioned | 2019-12-02T10:37:49Z | |
dc.date.available | 2019-12-02T10:37:49Z | |
dc.date.issued | 2014 | |
dc.identifier.isbn | 978-1-4939-0568-3 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/57504 | |
dc.description.abstract | The problem of confidence interval construction in nonparametric regression via the bootstrap is revisited. When an additive model holds true, the usual residual bootstrap is available but it often leads to confidence interval under-coverage | en |
dc.description.abstract | the case is made that this under-coverage can be partially corrected using predictive—as opposed to fitted—residuals for resampling. Furthermore, it has been unclear to date if a bootstrap approach is feasible in the absence of an additive model. The main thrust of this paper is to show how the transformation approach put forth by Politis (Test 22(2):183–221, 2013) in the related setting of prediction intervals can be found useful in order to construct bootstrap confidence intervals without an additive model. © Springer Science+Business Media New York 2014. | en |
dc.publisher | Springer New York LLC | en |
dc.source | Springer Proceedings in Mathematics and Statistics | en |
dc.source | 1st Conference of the International Society of Nonparametric Statistics, ISNPS 2012 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84919968824&doi=10.1007%2f978-1-4939-0569-0_25&partnerID=40&md5=f96e22c36cbfc48223a1be36ac009b0f | |
dc.subject | Statistics | en |
dc.subject | Financial data processing | en |
dc.subject | Non-parametric regression | en |
dc.subject | Resampling | en |
dc.subject | Confidence interval | en |
dc.subject | Model free | en |
dc.subject | Prediction interval | en |
dc.subject | Bootstrap approach | en |
dc.subject | Bootstrap confidence interval | en |
dc.subject | Model-free inference | en |
dc.subject | Nonparametric function estimation | en |
dc.title | Bootstrap confidence intervals in nonparametric regression without an additive model | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1007/978-1-4939-0569-0_25 | |
dc.description.volume | 74 | |
dc.description.startingpage | 271 | |
dc.description.endingpage | 282 | |
dc.author.faculty | Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Sponsors: Springer Science and Business Media | en |
dc.description.notes | The Bernoulli Society for Mathematical Statistics and Probability | en |
dc.description.notes | The Institute of Mathematical Statistics (IMS) | en |
dc.description.notes | The International Statistical Institute (ISI) | en |
dc.description.notes | The Nonparametric Statistics Section of the American Statistical Association (ASA) | en |
dc.description.notes | Conference code: 111829</p> | en |