Bivariate Local Join Count
Bivariate or no-colocation local join count (2019) only works when two events cannot happen in the same location (e.g., a zoning classification, or a case-control design). It can be used to identify negative spatial autocorrelation, i.e., evidence of spatial outliers. For more information, please read http://geodacenter.github.io/workbook/6a_local_auto/lab6a.html
function localBiJoinCount(
WeightResult w,
Array val1,
Array val2,
Number permutations,
String permutation_method,
NUmber significance_cutoff,
Number seed)
Name | Type | Description |
w | WeightResult | the WeightResult object created from weights function |
val1 | Array | the first numeric variable that contains the values for LISA statistics |
val1 | Array | the second numeric variable that contains the values for LISA statistics |
permutations | Number | the number of permutations for the LISA computation. Default: 999. |
permutation_method | String | the permutation method used for the LISA computation. Options are 'complete', 'lookup'. Default: 'lookup'. |
significance_cutoff | Number | the cutoff value for significance p-values to filter not-significant clusters. Default: 0.05. |
seed | Number | the seed for random number generator used in LISA statistics. Default: 123456789. |
Type | Description |
LisaResult | The LisaResult object contains the results of LISA computation: pvalues, clusters, lisa_values, neighbors, labels, colors |
Try it yourself in the playground (jsgeoda + deck.gl):