| dc.contributor.author | Garner, W. | en |
| dc.contributor.author | Politis, Dimitris Nicolas | en |
| dc.creator | Garner, W. | en |
| dc.creator | Politis, Dimitris Nicolas | en |
| dc.date.accessioned | 2019-12-02T10:35:13Z | |
| dc.date.available | 2019-12-02T10:35:13Z | |
| dc.date.issued | 2018 | |
| dc.identifier.issn | 1350-7265 | |
| dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/56844 | |
| dc.description.abstract | The asymptotic theory for the sample mean of a marked point process in d dimensions is established, allowing for the possibility that the underlying Poisson point process is inhomogeneous. A novel local block bootstrap method for resampling inhomogeneous Poisson marked point processes is introduced, and its consistency is proven for the sample mean and related statistics. Finite-sample simulations are carried out to complement the asymptotic results, and demonstrate the feasibility of the proposed methodology. © 2018 ISI/BS. | en |
| dc.source | Bernoulli | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026321871&doi=10.3150%2f16-BEJ889&partnerID=40&md5=9cf42a92f38a65ac5bc95cb42bfd8872 | |
| dc.subject | Stochastic processes | en |
| dc.subject | Resampling | en |
| dc.subject | Sample mean | en |
| dc.title | Local block bootstrap for inhomogeneous Poisson marked point processes | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.identifier.doi | 10.3150/16-BEJ889 | |
| dc.description.volume | 24 | |
| dc.description.issue | 1 | |
| dc.description.startingpage | 592 | |
| dc.description.endingpage | 615 | |
| 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 | Bernoulli | en |
