4.2 Multivariate Local Geary
Multivariate local geary (2019) is a multivariate extension of local geary which measures the extent to which neighbors in multiattribute space are also neighbors in geographical space. For more information, please read: https://geodacenter.github.io/workbook/6c_local_multi/lab6c.html
local_multigeary()
Synopsis
Short version:
float[] local_multigeary(anyarray vals, bytea weights)
Full version:
float[] local_multigeary(anyarray vals, bytea weights,
integer permutations,
character varying permutation_method,
float significance_cutoff,
integer cpu_threads,
integer seed)
Arguments
Name
Type
Description
vals
anyarray
an array of the numeric columns that contains the values for LISA statistics
weights
bytea
a 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'}
Cluster Indicators
The predefined values of the cluster indicators of multivariate local moran are:
Cluster indicator value
Description
Color
0
Not significant
#eeeeee
1
Positive
#b2182b
2
Negative
#67adc7
3
Undefined Value
#464646
4
Isolated
#999999
Examples
Apply local multivariate geary statistics on the variable ["hr60", "ue60", "dv60"] (homicide, unemployment, divorce rate 1960 in natregimes dataset)using queen contiguity weights "queen_w":
SELECT local_multigeary(ARRAY[hr60, ue60, dv60], queen_w) OVER() FROM natregimes;
local_multigeary
-------------------------------
{0.143230008312297,0.001,1}
{0.870354875283013,0.001,1}
{0.463879925600245,0.053,0}
...
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