| dc.contributor.author | Chang, Christopher C. | en |
| dc.contributor.author | Politis, Dimitris Nicolas | en |
| dc.creator | Chang, Christopher C. | en |
| dc.creator | Politis, Dimitris Nicolas | en |
| dc.date.accessioned | 2019-12-02T10:34:13Z | |
| dc.date.available | 2019-12-02T10:34:13Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/56577 | |
| dc.source.uri | https://nls.ldls.org.uk/welcome.html?ark:/81055/vdc_100031936856.0x000043 | |
| dc.subject | Data processing | en |
| dc.subject | Graphic methods | en |
| dc.subject | Mathematical statistics | en |
| dc.title | Robust Autocorrelation EstimationAAA | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.description.startingpage | 1 | |
| dc.description.endingpage | online | |
| 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.description.notes | <p>ID: 1003 | en |
| dc.description.notes | In: Journal of computational and graphical statistics, Vol. 25, no. 1 ( 2016), p.144-166. | en |
| dc.description.notes | Summary: AbstractIn this article, we introduce a new class of robust autocorrelation estimators based on interpreting the sample autocorrelation function as a linear regression. We investigate the efficiency and robustness properties of the estimators that result from employing three common robust regression techniques. We discuss the construction of robust autocovariance and positive definite autocorrelation estimates, and their application to AR model fitting. We perform simulation studies with various outlier configurations to compare the different estimators.</p> | en |
