I wish to incrementally find the neighbour distance which maximises Moran's I test statistic. I have read that the I values are not comparable across varying spatial weight matrices but that the z-value should be maximised instead. Where can I find/how can I compute the z-value in
spdep package? I don't see a z-value either in the value or in the structure of
lm.morantest printed to the console (same applies to
moran.test for a single variable):
library(spdep) lm.morantest(lm(pat_ct~pub_ct, sca_ct), w_dist, alternative="two.sided") #Global Moran I for regression residuals #data: #model: lm(formula = pat_ct ~ pub_ct, data = sca_ct) #weights: w_dist #Moran I statistic standard deviate = 12.155, p-value < 2.2e-16 #alternative hypothesis: two.sided #sample estimates: #Observed Moran I Expectation Variance # 3.556003e-02 -8.665431e-05 8.600474e-06 str(lm.morantest(lm(pat_ct~pub_ct, sca_ct), w_dist, alternative="two.sided")) #List of 6 # $ statistic : num [1, 1] 12.2 # ..- attr(*, "names")= chr "Moran I statistic standard deviate" # $ p.value : num [1, 1] 5.39e-34 # $ estimate : Named num [1:3] 3.56e-02 -8.67e-05 8.60e-06 # ..- attr(*, "names")= chr [1:3] "Observed Moran I" "Expectation" "Variance" # $ method : chr "Global Moran I for regression residuals" # $ alternative: chr "two.sided" # $ data.name : chr "\nmodel: lm(formula = pat_ct ~ pub_ct, data = sca_ct)\nweights: w_dist\n" # - attr(*, "class")= chr "htest"
I assume a minimal reproducible example is not required to answer this generic question.