hello,
I want to do a test for spatial correlation. I tried it with geary.test() but I don't understand the required input. x= a numeric vector the same length as the neighbours list in listw (my sampled data, I assume) listw= a listw object created for example by nb2listw (well when I check nb2listw() I get to "neighbours - an object of class nb" - but I couldn't figure out, what nb is or how I create such a class
with sp.mantel.mc {spdep} I have the same problem: listw created by nb2listw
isn't there a more straight forward method ;-) to check for spatial correlation? like x and y coordinates plus my sampled data?
This functions require a list of spatial weights for each geographical unit. To construct this list, you must firstly establish the neighborhood relationships (who are the neighbors of a point). There are different ways to construct this neighborhood: based on distances (dnearneigh), number of nearest neighbors (knearneigh)... Then, you must transform this neighborhood to weights (see nb2listw for example). Here is a small example requiring the tripack library based on tesselation and voronoi mosaic to create the neighboorhood:
xy=matrix(rnorm(20),5,2) z=rnorm(5) library(spdep)
mynb=tri2nb(xy) mylw=nb2listw(mynb)
geary.mc(z,mylw,10)
Monte-Carlo simulation of Geary's C
data: z weights: mylw number of simulations + 1: 11
There is no simplest method.....
statistic = 0.8384, observed rank = 2, p-value = 0.1818 alternative hypothesis: less
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