Extract eigenfunctions of a connectivity matrix for spatial filtering
make_EV(C, nsa = FALSE, threshold = 0.2, values = FALSE)
Daniel Griffith and Yongwan Chun. 2014. "Spatial Autocorrelation and Spatial Filtering." in M. M. Fischer and P. Nijkamp (eds.), Handbook of Regional Science. Springer.
A binary spatial weights matrix. See
Logical. Default of
nsa = FALSE excludes eigenvectors capturing negative spatial autocorrelation.
nsa = TRUE will result in a candidate set of EVs that contains eigenvectors representing positive and negative SA.
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).
Should eigenvalues be returned also? Defaults to
data.frame of eigenvectors for spatial filtering. If
values=TRUE then a named list is returned with elements
Returns a set of eigenvectors related to the Moran coefficient (MC), limited to those eigenvectors with |MC| >
nsa = TRUE or MC >
nsa = FALSE, optionally with corresponding eigenvalues.