`R/convenience-functions.R`

`make_EV.Rd`

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.

- 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`

.

A `data.frame`

of eigenvectors for spatial filtering. If `values=TRUE`

then a named list is returned with elements `eigenvectors`

and `eigenvalues`

.

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.