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Local Geary’s C (Anselin 1995) is defined as:

\[ c_i = \sum_jw_{ij}(x_i - x_j)^2, \]

where \(w_{ij}\)s are spatial weights from location \(i\) to location \(j\) and \(x\) is a variable at spatial location. This is generalized to multiple variables in (Anselin 2019):

\[ c_{k,i} = \sum_{v=1}^k c_{v,i}, \]

where there are \(k\) variables. This vignette demonstrates usage of multivariate local Geary’s C.

Below is a list of vignettes that use multivariate local Geary’s C. The links point to the sections that use multivariate local Geary’s C. The corresponding Google Colab notebooks are also linked to. The list is sorted by technology.

Vignette Colab Notebook Description
Multivariate local Geary’s C Colab Notebook Multivariate local Geary’s C on highly variable genes in mouse skeletal muscle Visiumd dataset


Anselin, Luc. 1995. “Local Indicators of Spatial Association—LISA.” Geogr. Anal. 27 (2): 93–115.
———. 2019. “A Local Indicator of Multivariate Spatial Association: Extending Geary’s c.” Geogr. Anal. 51 (2): 133–50.