You can also fit a variogram to the residuals using the gstat package and then record the nugget and sill variation (see http://www.gstat.org/manual/node7.html). I do not know how to test that the nugget variation is statistically significant from the sill variation. You could split the variogram cloud into closer points and more distant points and then run some statistical tests on the two sub-sets (e.g. the t-test). But where to put a boundary between closer/more distant points?
Tom Hengl http://spatial-analyst.net -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Geertje Van der Heijden Sent: vrijdag 26 oktober 2007 18:12 To: r-sig-geo@stat.math.ethz.ch Subject: [R-sig-Geo] Spdep: help needed calculating Moran's I Hi, I have just posted the same question on the general R help mailing list, but thought that this list might be more appropriate. I am a new user of R. Here is my problem: I have 58 sites from across South America. I have done a regression analysis to relate environmental and biogeographical variables to species richness and want to test whether my residuals are autocorrelated. As far as I understand the Moran's I, I have to take all possible combinations between all points into account to test this. So I have used dnearneigh() with the lower boundary set to 0 and the upper boundary set arbitrarily high to make sure all connections are included. >coords <- as.matrix(cbind(lowland$long, lowland$lat)) >coord.nb <- dnearneigh(coords, 0, 10000, longlat=TRUE) >coord.list <- nb2listw(coord.nb, style="W") >lianasp.lm <- lm(lianasprich ~ log(averdist) + dsl + lianadens + wooddens) >lm.morantest(lianasp.lm, coord.list, alternative="two.sided") However, this gives me a Moran's I which is exactly the same as the expected Moran's I (and hence a p-value of 1). If I change the lower or upper boundary slightly so that not all possible links are taken into account, the value is different, but still really near to the expected Moran's I. I don't understand why these values are or the same or nearly so. I am new to spatial statistics, so this might me a really basic question and my appologies if it is, but I am generally a bit at a loss now about the Moran's I and I am wondering if I have calculated it right. Have used to right method to convert my coordinates into neighbourhood distances (and if not, which method should I have used) and am I understanding and calculation the Moran's I correctly? Any help would be greatly appreciated. Many thanks, Geertje ~~~~ Geertje van der Heijden PhD student Tropical Ecology School of Geography University of Leeds Leeds LS2 9JT Tel: (+44)(0)113 3433345 Email: [EMAIL PROTECTED] [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo