Space‐time Multi Type Log Gaussian Cox Processes with a View to Modelling Weeds
Anders Brix and
Jesper Moller
Scandinavian Journal of Statistics, 2001, vol. 28, issue 3, 471-488
Abstract:
Log Gaussian Cox processes as introduced in Moller et al. (1998) are extended to space‐time models called log Gaussian Cox birth processes. These processes allow modelling of spatial and temporal heterogeneity in time series of increasing point processes consisting of different types of points. The models are shown to be easy to analyse yet flexible enough for a detailed statistical analysis of a particular agricultural experiment concerning the development of two weed species on an organic barley field. Particularly, the aspects of estimation, model validation and intensity surface prediction are discussed.
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (18)
Downloads: (external link)
https://doi.org/10.1111/1467-9469.00249
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:28:y:2001:i:3:p:471-488
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898
Access Statistics for this article
Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist
More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().