Analyzing spatial count data, with an application to weed counts

被引：4
|
作者：
Kruijer, Willem
Stein, Alfred
Schaafsma, Willem
Heijting, Sanne
机构：
[1] Vrije Univ Amsterdam, Dept Math, NL-1081 HV Amsterdam, Netherlands
[2] Int Inst Geo Informat Sci & Earth Observat, NL-7500 AA Enschede, Netherlands
[3] Univ Groningen, Dept Math, NL-9700 AV Groningen, Netherlands
[4] Univ Wageningen, Dept Crop & Weed Ecol, NL-6700 AK Wageningen, Netherlands
来源：
ENVIRONMENTAL AND ECOLOGICAL STATISTICS | 2007年 / 14卷 / 04期
关键词：
Markov random fields; anisotropy; multivariate count data; precision agriculture;
D O I：
10.1007/s10651-007-0027-y
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Count data on a lattice may arise in observational studies of ecological phenomena. In this paper a hierarchical spatial model is used to analyze weed counts. Anisotropy is introduced, and a bivariate extension of the model is presented.
引用
收藏
页码：399 / 410
页数：12
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