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Nonparametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK
Author(s) -
Diggle Peter,
Zheng Pingping,
Durr Peter
Publication year - 2005
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2005.05373.x
Subject(s) - multivariate statistics , nonparametric statistics , statistics , point process , econometrics , kernel (algebra) , bovine tuberculosis , spatial epidemiology , mathematics , spatial analysis , multivariate analysis , computer science , tuberculosis , epidemiology , medicine , mycobacterium tuberculosis , mycobacterium bovis , pathology , combinatorics
Summary. 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.