make_EV function

Prepare data for spatial filtering

Prepare data for spatial filtering

Source

Daniel Griffith and Yongwan Chun. 2014. "Spatial Autocorrelation and Spatial Filtering." in M. M. Fischer and P. Nijkamp (eds.), Handbook of Regional Science. Springer.

make_EV(C, nsa = FALSE, threshold = 0.2, values = FALSE)

Arguments

  • C: A binary spatial weights matrix. See shape2mat.
  • nsa: Logical. Default of nsa = FALSE excludes eigenvectors capturing negative spatial autocorrelation. Setting nsa = TRUE will result in a candidate set of EVs that contains eigenvectors representing positive and negative SA.
  • threshold: Defaults to threshold=0.2 to exclude eigenvectors representing spatial autocorrelation levels that are less than threshold times the maximum possible Moran coefficient achievable for the given spatial connectivity matrix. If theshold = 0, all eigenvectors will be returned (however, the eigenvector of constants (with eigenvalue of zero) will be dropped automatically).
  • values: Should eigenvalues be returned also? Defaults to FALSE.

Returns

A data.frame of eigenvectors for spatial filtering. If values=TRUE then a named list is returned with elements eigenvectors and eigenvalues.

Details

Returns a set of eigenvectors related to the Moran coefficient (MC), limited to those eigenvectors with |MC| > threshold if nsa = TRUE or MC > threshold if nsa = FALSE, optionally with corresponding eigenvalues.

Examples

library(ggplot2) data(georgia) C <- shape2mat(georgia, style = "B") EV <- make_EV(C) head(EV) ggplot(georgia) + geom_sf(aes(fill = EV[,1])) + scale_fill_gradient2()

See Also

stan_esf , mc

  • Maintainer: Connor Donegan
  • License: GPL (>= 3)
  • Last published: 2024-12-04