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

Diggle, P. J. and Zheng, P. and 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). pp. 645-658. ISSN 0035-9254

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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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of the Royal Statistical Society: Series C (Applied Statistics)
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? bovine tuberculosis • monte carlo test • multivariate point process • spatial segregationstatistics and probabilitystatistics, probability and uncertaintyr medicine (general) ??
ID Code:
19374
Deposited By:
Deposited On:
20 Nov 2008 12:00
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 09:43