Geary's C

Geary's C is a measure of spatial autocorrelation or an attempt to determine if adjacent observations of the same phenomenon are correlated. Spatial autocorrelation is more complex than autocorrelation because the correlation is multi-dimensional and bi-directional.

Geary's C is defined as

${\displaystyle C={\frac {(N-1)\sum _{i}\sum _{j}w_{ij}(x_{i}-x_{j})^{2}}{2W\sum _{i}(x_{i}-{\bar {x}})^{2}}}}$

where ${\displaystyle N}$ is the number of spatial units indexed by ${\displaystyle i}$ and ${\displaystyle j}$; ${\displaystyle x}$ is the variable of interest; ${\displaystyle {\bar {x}}}$ is the mean of ${\displaystyle x}$; ${\displaystyle w_{ij}}$ is a matrix of spatial weights with zeroes on the diagonal (i.e., ${\displaystyle w_{ii}=0}$); and ${\displaystyle W}$ is the sum of all ${\displaystyle w_{ij}}$.

The value of Geary's C lies between 0 and some unspecified value greater than 1. Values significantly lower than 1 demonstrate increasing positive spatial autocorrelation, whilst values significantly higher than 1 illustrate increasing negative spatial autocorrelation.

Geary's C is inversely related to Moran's I, but it is not identical. Moran's I is a measure of global spatial autocorrelation, while Geary's C is more sensitive to local spatial autocorrelation.

Geary's C is also known as Geary's contiguity ratio or simply Geary's ratio.[1]

This statistic was developed by Roy C. Geary.[2]