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Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK.

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Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. / Diggle, P. J.; Zheng, P.; Durr, P. A.
In: Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol. 54, No. 3, 2005, p. 645-658.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Diggle, PJ, Zheng, P & Durr, PA 2005, 'Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK.', Journal of the Royal Statistical Society: Series C (Applied Statistics), vol. 54, no. 3, pp. 645-658. https://doi.org/10.1111/j.1467-9876.2005.05373.x

APA

Diggle, P. J., Zheng, P., & Durr, P. A. (2005). Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. Journal of the Royal Statistical Society: Series C (Applied Statistics), 54(3), 645-658. https://doi.org/10.1111/j.1467-9876.2005.05373.x

Vancouver

Diggle PJ, Zheng P, Durr PA. Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. Journal of the Royal Statistical Society: Series C (Applied Statistics). 2005;54(3):645-658. doi: 10.1111/j.1467-9876.2005.05373.x

Author

Diggle, P. J. ; Zheng, P. ; Durr, P. A. / Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. In: Journal of the Royal Statistical Society: Series C (Applied Statistics). 2005 ; Vol. 54, No. 3. pp. 645-658.

Bibtex

@article{f57bc1d7df0a462787b523a17e5427c9,
title = "Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK.",
abstract = "The paper is motivated by a problem in veterinary epidemiology, in which spatially referenced breakdowns of bovine tuberculosis are classified according to their genotype and year of occurrence. We develop a nonparametric method for addressing spatial segregation in the resulting multivariate spatial point process, with associated Monte Carlo tests for the null hypothesis that different genotypes are randomly intermingled and no temporal changes in spatial segregation. Our spatial segregation estimates use a kernel regression method with bandwidth selected by a multivariate cross-validated likelihood criterion.",
keywords = "Bovine tuberculosis • Monte Carlo test • Multivariate point process • Spatial segregation",
author = "Diggle, {P. J.} and P. Zheng and Durr, {P. A.}",
year = "2005",
doi = "10.1111/j.1467-9876.2005.05373.x",
language = "English",
volume = "54",
pages = "645--658",
journal = "Journal of the Royal Statistical Society: Series C (Applied Statistics)",
issn = "0035-9254",
publisher = "Wiley-Blackwell",
number = "3",

}

RIS

TY - JOUR

T1 - Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK.

AU - Diggle, P. J.

AU - Zheng, P.

AU - Durr, P. A.

PY - 2005

Y1 - 2005

N2 - The paper is motivated by a problem in veterinary epidemiology, in which spatially referenced breakdowns of bovine tuberculosis are classified according to their genotype and year of occurrence. We develop a nonparametric method for addressing spatial segregation in the resulting multivariate spatial point process, with associated Monte Carlo tests for the null hypothesis that different genotypes are randomly intermingled and no temporal changes in spatial segregation. Our spatial segregation estimates use a kernel regression method with bandwidth selected by a multivariate cross-validated likelihood criterion.

AB - The paper is motivated by a problem in veterinary epidemiology, in which spatially referenced breakdowns of bovine tuberculosis are classified according to their genotype and year of occurrence. We develop a nonparametric method for addressing spatial segregation in the resulting multivariate spatial point process, with associated Monte Carlo tests for the null hypothesis that different genotypes are randomly intermingled and no temporal changes in spatial segregation. Our spatial segregation estimates use a kernel regression method with bandwidth selected by a multivariate cross-validated likelihood criterion.

KW - Bovine tuberculosis • Monte Carlo test • Multivariate point process • Spatial segregation

U2 - 10.1111/j.1467-9876.2005.05373.x

DO - 10.1111/j.1467-9876.2005.05373.x

M3 - Journal article

VL - 54

SP - 645

EP - 658

JO - Journal of the Royal Statistical Society: Series C (Applied Statistics)

JF - Journal of the Royal Statistical Society: Series C (Applied Statistics)

SN - 0035-9254

IS - 3

ER -