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I am attempting to test for spatial-autocorrelation among regression residuals via Moran's I in R using the 'spdep' package. While creating the spatial weights, changing the value of k changes the result of my Moran's I test. I have 1582 regions, and running the following code:

>knn2nb(knearneigh(spoints,k=100))

returns:

>Neighbour list object:
Number of regions: 1582 
Number of nonzero links: 158200 
Percentage nonzero weights: 6.321113 
Average number of links: 100 
Non-symmetric neighbours list

I came across a semi-recent article: https://cran.r-project.org/web/packages/spdep/vignettes/nb.pdf that uses 8.717% non-zero weights, and I'm wondering if there is a best practice for finding the sweet spot for this type of procedure.

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