Thayse Nery
2016-Nov-10 08:20 UTC
[R] Moran's I test for spatial autocorrelation - "spdep" package
Dear all, I would like to use the Moran's I test for residual spatial autocorrelation. My dataset is in the long format [70000 , 17] and represents a time series of Land Use and Land Cover Changes. Since I have identical x and y coordinates, I am having trouble in performing the Moran's test using the "spdep" package. I am able to perform the Moran's test if I consider only one year at time, but I need to perform the analyse for the whole dataset. My dataframe is called trainData. Below are the steps I have done: xy <- as.matrix(trainData [, c(5:6)]) neighb.k1 <- knn2nb(knearneigh(xy , k=2, longlat=FALSE)) distance <- max(unlist(nbdists(neighb.k1, xy, longlat=FALSE))) summary(distance) # Error in assign neighbors based on a specified distance, all values = 0 #Because of this error I am not able to continue the analysis # Min. 1st Qu. Median Mean 3rd Qu. Max. # 0 0 0 0 0 0 gc.nb <- dnearneigh(xy, 0, distance, longlat=FALSE) ### 2. Assign weights to the areas that are linked by by creating a spatial weights matrix MyData_neighb_w <- nb2listw(gc.nb, zero.policy=T) # ## 3. Run statistical test to examine spatial autocorrelation (Moran's I on the DV) DV_SpatialAut <- moran.test(trainData$currentState, listw=MyData_neighb_w) ### 4. Test the Spatial autocorrelation in residuals: ## 4.1. Run the Multinomial Logit Model FitVglm is the Model ## Calculate the weighted matrix for the residuals from multinomial logit model MyDataFinal2 <- MyDataFinal MyDataFinal2$mlmresid <- residuals(FitVgamx) lm.morantest(FitVgamx, resfun=MyData_neighb_w) Is it possible to test for residual spatial autocorrelation for a time series data with identical x and y coordinates using the "spdep" package? Thank you in advance for any help you can provide. Regards Thayse Nery PhD. Student The University of Western Australia [[alternative HTML version deleted]]