Analyzing spatial count data, with an application to weed counts

Willem Kruijer; Alfred Stein; Willem Schaafsma; Sanne Heijting

doi:10.1007/s10651-007-0027-y

Analyzing spatial count data, with an application to weed counts

Willem Kruijer^*, Alfred Stein, Willem Schaafsma, Sanne Heijting

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

6 Citations (Scopus)

17 Downloads (Pure)

Abstract

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.

Original language	English
Pages (from-to)	399-410
Number of pages	12
Journal	Environmental and ecological statistics
Volume	14
Issue number	4
DOIs	https://doi.org/10.1007/s10651-007-0027-y
Publication status	Published - Dec 2007

Keywords

Anisotropy
Markov random fields
Multivariate count data
Precision agriculture
ADLIB-ART-2590
EOS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s10651-007-0027-yLicence: CC BY

ArticleFinal published version, 301 KBLicence: CC BY

Cite this

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title = "Analyzing spatial count data, with an application to weed counts",

abstract = "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.",

keywords = "Anisotropy, Markov random fields, Multivariate count data, Precision agriculture, ADLIB-ART-2590, EOS",

author = "Willem Kruijer and Alfred Stein and Willem Schaafsma and Sanne Heijting",

year = "2007",

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T1 - Analyzing spatial count data, with an application to weed counts

AU - Kruijer, Willem

AU - Stein, Alfred

AU - Schaafsma, Willem

AU - Heijting, Sanne

PY - 2007/12

Y1 - 2007/12

N2 - 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.

AB - 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.

KW - Anisotropy

KW - Markov random fields

KW - Multivariate count data

KW - Precision agriculture

KW - ADLIB-ART-2590

KW - EOS

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U2 - 10.1007/s10651-007-0027-y

DO - 10.1007/s10651-007-0027-y

M3 - Article

SN - 1352-8505

VL - 14

SP - 399

EP - 410

JO - Environmental and ecological statistics

JF - Environmental and ecological statistics

IS - 4

ER -

Analyzing spatial count data, with an application to weed counts

Abstract

Keywords

UN SDGs

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