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    • Local Getis-Ord G
    • Local Join Count
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  • Multivariate Local Spatial Autocorrelation
    • Local Neighbor Match Test
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  • API REFERENCE
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  • localG()
  • localGStar()
  • Arguments
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  1. Local Spatial Autocorrelation

Local Getis-Ord G

PreviousLocal GearyNextLocal Join Count

Last updated 3 years ago

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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:

In contrast to the Local Moran and Local Geary statistics, the Getis-Ord approach does not consider spatial outliers.

CONTENTS

  1. localG() and localGStar()

localG()

function localG(
    WeightResult w,
    Array val,
    Number permutations, 
    String permutation_method,
    NUmber significance_cutoff, 
    Number seed)

localGStar()

function localGStar(
    WeightResult w,
    Array val,
    Number permutations, 
    String permutation_method,
    NUmber significance_cutoff, 
    Number seed)

Arguments

Name

Type

Description

w

WeightResult

the WeightResult object created from weights function

val

Array

the values of a selected variable

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.

Return

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):

https://geodacenter.github.io/workbook/6b_local_adv/lab6b.html#getis-ord-statistics