Hi. Does anyone have an example of estimating Moran's I from a file with point (not polygon) data? I'm getting close(r) but I still have a few problems.
Here's my code so far: library(spdep) ctpoints <- read.csv("c:\\Georgia\\xy.csv", header=TRUE) # only two columns containing the long-lat data str(ctpoints) plot(ctpoints) neigh <- tri2nb(ctpoints) plot (neigh, ctpoints) nblist <- nb2listw(neigh, glist=NULL, style="W", zero.policy=FALSE) ????? <- spNamedVec("?????", ctpoints) gamoran <- moran(?????, nblist, n, S0, zero.policy=FALSE, NAOK=FALSE) I'm not sure what goes where I have "?????". And yup, I did a help(spNamedVec) but I'm not sure how to translate that material to my case. Eventually, I would like to run a number of Poisson or negative binomial regressions linking avian species richness to landscape variables around the same points where I surveyed birds. See http://web6.duc.auburn.edu/~stratja/georgia.pdf (map showing points on a LANDSAT map) to get an idea of the proximity and location of points. Since I will eventually incorporate spatial effects into my regressions should I change the file to one that contains the coordinates, the bird data, and the landscape data? Many thanks (again), Jeff **************************************** Jeffrey A. Stratford, Ph.D. Postdoctoral Associate 331 Funchess Hall Department of Biological Sciences Auburn University Auburn, AL 36849 334-329-9198 FAX 334-844-9234 http://www.auburn.edu/~stratja _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo