3.3 Local Getis-Ord G
The local Getis-Ord statistic is a ratio of the weighted average of the values in the neighboring locations to the sum of all values. It is called local g or local g*, when not including the value at the location. In local g/g*, a value larger than the mean (or, a positive value for a standardized z-value) suggests a High-High cluster or hot spot, a value smaller than the mean (or, negative for a z-value) indicates a Low-Low cluster or cold spot. For more information, please read: https://geodacenter.github.io/workbook/6b_local_adv/lab6b.html#getis-ord-statistics
In contrast to the Local Moran and Local Geary statistics, the Getis-Ord approach does not consider spatial outliers.
CONTENTS
local_g() and local_gstar()
local_g(), local_gstar()
local_g() or local_gstar() is a PostgreSQL WINDOW function. Please call it with an OVER clause.
Synopsis
Short version:
Full version:
Arguments
Name
Type
Description
val
numeric
the numeric column that contains the values for LISA statistics
weights
bytea
the bytea column that stores the spatial weights information
permutations
integer
the number of permutations for the LISA computation. Default: 999.
permutation_method
character varying
the permutation method used for the LISA computation. Options are 'complete', 'lookup'. Default: 'lookup'.
significance_cutoff
float
the cutoff value for significance p-values to filter not-significant clusters. Default: 0.05.
cpu_threads
integer
the number of CPU threads used for parallel LISA computation. Default: 6.
seed
integer
the seed for random number generator used in LISA statistics. Default: 123456789.
Return
Type
Description
float[]
an array contains 3 values, which are {'lisa value', 'pseudo-p value' and 'cluster indicator'}
Examples
Apply local_g on the variable "hr60" (homicide rate 1960 in natregimes dataset) using queen contiguity weights "queen_w":
Please see chapter 'Contiguity Based Weights' for how to create a Queen contiguity weights.
One can specify the arguments of local g using the full version of local_g() function. For example, apply local moran statistics using 9,999 permutations, significance cutoff value 0.01:
Cluster Indicators
The predefined values of the cluster indicators of local g/g* are:
Cluster indicator value
Description
Color
0
Not significant
#eeeeee
1
High-High
#ff0000
2
Low-Low
#0000ff
3
Undefined Value
#464646
4
Isolated
#999999
One can extract the cluster indicators and make a local g/g* cluster map using the 'Color" values in the table above:
Or by extracting the pseudo-p values to make a significance map:
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