Spatial autocorrelation — spatial

This function calculate some spatial autocorrelations for a sample of networks at different orders (distances).

Usage

spatial_cor(
  A,
  V,
  measures = c("covariance", "correlation", "moran", "geary"),
  mean = TRUE,
  diag = FALSE,
  distance1 = TRUE,
  rowstand = FALSE,
  scale = FALSE
)

Arguments

A: A symmetric matrix
V: A vector
measures: Whether to use the Covariance covariance (default), Correlation correlation, Moran I moran or Geary's C geary
mean: Whether to use the mean of the vector for the measures
diag: Whether to consider the diagonal of the matrix for the measures
distance1: Whether to return only the spatial autocorrelation considering the actor at distance 1
rowstand: Whether to use the row-standardization to estimate Moran I (Anselin, 1995)
scale: Whether to scale Moran I (Anselin, 1995)

Value

This function return the global spatial autocorrelation. Multiple orders can also be computed.

References

Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical analysis, 27(2), 93-115.

Geary, R.C. (1954). “The Contiguity Ratio and Statistical Mapping.” The Incorporated Statistician, 5: 115-145.

Moran, P.A.P. (1950). “Notes on Continuous Stochastic Phenomena.” Biometrika, 37: 17-23.

Examples

A <- matrix(c(
  0, 0, 1, 1,
  0, 0, 1, 0,
  1, 0, 0, 0,
  1, 0, 1, 0
), byrow = TRUE, ncol = 4)
V <- c(2, 2, 1, 1)

spatial_cor(A, V, measures = c("moran"))
#> [1] -0.6666667