Dear all,
I am using the spdep package to compute Local Moran Index. My problem is that I am using 3D coordinates (x,y,z), and I would like to compute the k-nearest neighbours (k=10) for each point in my 3D space. I have already done this in 2D, by doing the following: >neighs_k <- knn2nb(knearneigh(as.matrix(full), k = 10)) > neighs_mat_k <- nb2listw(neighs_k style = "W", zero.policy = TRUE) And then I can easily proceed using the neighs_mat_k object. However, when using x,y,z coordinates I can't run the knearneigh() function on it. I tried converting my data to a distance matrix and using mat2listw() function like this: >D <- as.matrix(dist(full, diag=FALSE, upper=FALSE)) >test1 <- mat2listw(D) ...but now I don't know how to retrieve the k-nearest weights from my test1 object (which would correspond to k-nearest neighbours) without changing the class of test1, which is: > class(test1) [1] "listw" "nb" ## and contains...: > ls(test1) [1] "neighbours" "style" "weights" How should I do this? Is this even the right way to proceed? Thanks all in advance!! Best wishes, Juan [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.