API reference

Gamma Statistic

esda.Gamma(y, w[, operation, standardize, …])

Gamma index for spatial autocorrelation

Geary Statistic

esda.Geary(y, w[, transformation, permutations])

Global Geary C Autocorrelation statistic

Getis-Ord Statistics

esda.G(y, w[, permutations])

Global G Autocorrelation Statistic

esda.G_Local(y, w[, transform, …])

Generalized Local G Autocorrelation

Join Count Statistics

esda.Join_Counts(y, w[, permutations])

Binary Join Counts

Moran Statistics

esda.Moran(y, w[, transformation, …])

Moran’s I Global Autocorrelation Statistic

esda.Moran_BV(x, y, w[, transformation, …])

Bivariate Moran’s I

esda.Moran_BV_matrix(variables, w[, …])

Bivariate Moran Matrix

esda.Moran_Local(y, w[, transformation, …])

Local Moran Statistics

esda.Moran_Local_BV(x, y, w[, …])

Bivariate Local Moran Statistics

esda.Moran_Rate(e, b, w[, adjusted, …])

Adjusted Moran’s I Global Autocorrelation Statistic for Rate Variables [AR99]

esda.Moran_Local_Rate(e, b, w[, adjusted, …])

Adjusted Local Moran Statistics for Rate Variables [Assuncao1999]

Spatial Pearson Statistics

esda.Spatial_Pearson([connectivity, …])

Global Spatial Pearson Statistic

esda.Local_Spatial_Pearson([connectivity, …])

Local Spatial Pearson Statistic

Modifiable Areal Unit Tests

esda.Smaup(n, k, rho)

S-maup: Statistical Test to Measure the Sensitivity to the Modifiable Areal Unit Problem

Utility Functions

esda.fdr(pvalues[, alpha])

Calculate the p-value cut-off to control for the false discovery rate (FDR) for multiple testing.