Hi,
I am trying to test the random labeling hypothesis with my data. I have a
point pattern of bird nests and each nest has a mark that it is either predated
or not-predated. I want to test the null hypothesis that the K distribution of
predation events is equal to the K distribution of all events (nests). This
is the code I am using:
Kdif <- function(X,...,i) {
Kidot <- Kdot(X,...,i=i)
K <- Kest(X,...)
dif <- eval.fv(Kidot-K)
return(dif)
}
E <- envelope(ppp, Kdif, nsim=100, i="Predated",
simulate=expression(rlabel(ppp)))
plot(E, main="clustering of predation events")
I got this code from the 'Analazing spatial patterns in R Workshop notes', and
it works fine, but not sure I understand exactly what it means. Specifically I
want to make sure that the Kidot is just looking at the distribution of
predation events, but I am not sure if it is doing this. What does
Kdot(X,...,i=i) mean exactly? It is much appreciated if anyone can help me
understand this. Thank you. Karla
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