Kernel density estimation for spatial processes : The L1 theory
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 61-75 |
| Journal / Publication | Journal of Multivariate Analysis |
| Volume | 88 |
| Issue number | 1 |
| Publication status | Published - Jan 2004 |
| Externally published | Yes |
Link(s)
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. © 2003 Elsevier Science (USA). All rights reserved.
Research Area(s)
- Bandwidth, Kernel density estimator, L1 theory, Spatial linear or nonlinear processes
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
Kernel density estimation for spatial processes: The L1 theory. / Hallin, Marc; Lu, Zudi; Tran, Lanh T.
In: Journal of Multivariate Analysis, Vol. 88, No. 1, 01.2004, p. 61-75.
In: Journal of Multivariate Analysis, Vol. 88, No. 1, 01.2004, p. 61-75.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
