Show simple item record

dc.contributor.authorGluhovsky, A.en
dc.contributor.authorZihlbauer, M.en
dc.contributor.authorPolitis, Dimitris Nicolasen
dc.creatorGluhovsky, A.en
dc.creatorZihlbauer, M.en
dc.creatorPolitis, Dimitris Nicolasen
dc.date.accessioned2019-12-02T10:35:21Z
dc.date.available2019-12-02T10:35:21Z
dc.date.issued2005
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/56876
dc.description.abstractProblems of practical implementation of the computer intensive subsampling methodology are addressed by Monte Carlo simulations of a situation typical for atmospheric time series. The motivating data were collected under Lake-Effect Snow Studies Project in the winter of 1983-1984 over Lake Michigan. Certain enhancements of subsampling methodology are suggested specifically on the issue of optimal block size choice. © 2005 Taylor & Francis Ltd.en
dc.sourceJournal of Statistical Computation and Simulationen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-27844565702&doi=10.1080%2f00949650410001729409&partnerID=40&md5=b58c684927019626cbc6f8175486aae5
dc.subjectTime seriesen
dc.subjectNonparametric estimationen
dc.subjectConfidence intervalsen
dc.subjectSubsamplingen
dc.subjectAtmospheric data analysisen
dc.titleSubsampling confidence intervals for parameters of atmospheric time series: Block size choice and calibrationen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1080/00949650410001729409
dc.description.volume75
dc.description.issue5
dc.description.startingpage381
dc.description.endingpage389
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :8</p>en
dc.source.abbreviationJ.Stat.Comput.Simul.en


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record