You can also have a look at:
DIGGLE P, ZHENG PP & DURR P (2005) Nonparametric 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, 645-658.
(The method is already implemented in R: spatialkernel)
With regards to the use of the bivariate K-function yu can find similar
applications to yours in:
FORTIN MJ & DALE MRT (2005) Spatial analysis: A guide for ecologists,
1st Edn. Cambridge University Press, Cambridge, UK.
berto costa rica wrote:
Dear list,
I want to assess if a series of cases (farms positive for a disease)
are spatially clustered by comparing them to the general population
(the total number of farms) in a given region. For that I would like
to know if it is statistically correct to use the bivariate (also
known as cross) k-function, considering cases as element 1 and general
population (all farms, including the cases) as element 2. I am using
splancs (k12hat function) in R. I know that you can do the difference
of k-functions but I would like to know if the use of the bivariate
k-function is correct.
If it is statistically correct, can I conclude that the positive farms
are clustered/dispersed compared to the total population (using label
permutation)?
Thanks in advance for your help
albert
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