[R] Moran's I test for spatial autocorrelation - "spdep" package
thayse.nery at hotmail.com
Thu Nov 10 09:20:49 CET 2016
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)))
# 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)
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.
The University of Western Australia
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