dc.contributor.author | Pan, L. | en |
dc.contributor.author | Politis, Dimitris Nicolas | en |
dc.creator | Pan, L. | en |
dc.creator | Politis, Dimitris Nicolas | en |
dc.date.accessioned | 2019-12-02T10:37:14Z | |
dc.date.available | 2019-12-02T10:37:14Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/57350 | |
dc.description.abstract | In order to construct prediction intervals without the cumbersome-and typically unjustifiable-assumption of Gaussianity, some form of resampling is necessary. The regression set-up has been well-studied in the literature but time series prediction faces additional difficulties. The paper at hand focuses on time series that can be modeled as linear, nonlinear or nonparametric autoregressions, and develops a coherent methodology for the construction of bootstrap prediction intervals. Forward and backward bootstrap methods using predictive and fitted residuals are introduced and compared. We present detailed algorithms for these different models and show that the bootstrap intervals manage to capture both sources of variability, namely the innovation error as well as estimation error. In simulations, we compare the prediction intervals associated with different methods in terms of their achieved coverage level and length of interval. © 2016 Published by Elsevier B.V. | en |
dc.source | Journal of Statistical Planning and Inference | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974528096&doi=10.1016%2fj.jspi.2014.10.003&partnerID=40&md5=8c643848c49b7a551175bd0b53b117e2 | |
dc.subject | Time series | en |
dc.subject | Forecasting | en |
dc.subject | Confidence intervals | en |
dc.title | Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1016/j.jspi.2014.10.003 | |
dc.description.volume | 177 | |
dc.description.startingpage | 1 | |
dc.description.endingpage | 27 | |
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 | Article | en |
dc.source.abbreviation | J.Stat.Plann.Inference | en |