[R-sig-Geo] Moran's I test for spatial autocorrelation - "spdep" package

[Thayse Nery]

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.



Thayse Nery

PhD. Student
School of Agricultural and Resource Economics (M089)
The University of Western Australia

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