Kernel density estimation for spatial processes: the L_1 theory
| dc.contributor.author | Hallin, M. | |
| dc.contributor.author | Lu, Zudi | |
| dc.contributor.author | Tran, L. | |
| dc.date.accessioned | 2017-01-30T11:17:31Z | |
| dc.date.available | 2017-01-30T11:17:31Z | |
| dc.date.created | 2010-03-29T20:04:53Z | |
| dc.date.issued | 2004 | |
| dc.identifier.citation | Hallin, Marc and Lu, Zudi and Tran, Lanh T. 2004. Kernel density estimation for spatial processes: the L_1 theory. Journal of Multivariate Analysis. 88 (1): pp. 61-75. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/10233 | |
| dc.identifier.doi | 10.1016/S0047-259X(03)00060-5 | |
| dc.description.abstract |
The purpose of this paper is to investigate kernel density estimators for spatial processes with linear or nonlinear structures. Sufficient conditions for such estimators to converge in L1 are obtained under extremely general, verifiable conditions. The results hold for mixing as well as for nonmixing processes. Potential applications include testing for spatial interaction, the spatial analysis of causality structures, the definition of leading/lagging sites, the construction of clusters of comoving sites, etc. | |
| dc.publisher | Elsevier | |
| dc.subject | Spatial linear or nonlinear processes | |
| dc.subject | L1 theory | |
| dc.subject | Kernel density estimator | |
| dc.subject | Bandwidth | |
| dc.title | Kernel density estimation for spatial processes: the L_1 theory | |
| dc.type | Journal Article | |
| dcterms.source.volume | 88 | |
| dcterms.source.startPage | 61 | |
| dcterms.source.endPage | 75 | |
| dcterms.source.issn | 0047-259X | |
| dcterms.source.title | Journal of Multivariate Analysis | |
| curtin.note |
The link to the journal’s home page is: | |
| curtin.accessStatus | Open access via publisher | |
| curtin.faculty | School of Science and Computing | |
| curtin.faculty | Department of Mathematics and Statistics | |
| curtin.faculty | Faculty of Science and Engineering |