4.5 Multivariate Quantile LISA

Multivariate Quantile LISA (2019) is a type of local spatial autocorrelation that applies multivariate local join count statistics to quantiles of multiple continuous variables. For each continuous variable, it is converted to a binary variable that takes the value of 1 for a specific quantile. For more information, please read https://geodacenter.github.io/workbook/6d_local_discrete/lab6d.html#quantile-lisa

multi_quantile_lisa()

multi_quantile_lisa() is a PostgreSQL WINDOW function. Please call it with an OVER clause.

Synopsis

Short version:

float[] multi_quantile_lisa(integer[] ks, integer[] qs[], anyarray vals, bytea weights)

Full version:

float[] multi_quantile_lisa(integer[] ks, integer[] qs[], anyarray vals, bytea weights,
    integer permutations, 
    character varying permutation_method,
    float significance_cutoff, 
    integer cpu_threads, 
    integer seed)

Arguments

Name	Type	Description
ks	integer[]	an array of integer numbers that specify quantiles for each variable
qs	integer[]	an array of integer numbers that specify which quantile is used for each variable
vals	anyarray	an array of numeric columns 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 {'local join count', 'pseudo-p value', 'number of neighbors'}

The results do NOT have 'category indicator'.