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Local G*

Source: R/localG-star.R
local_gstar.Rd

Calculate the local Gi* statistic.

Usage

local_gstar(x, nb, wt, alternative = "two.sided", ...)

local_gstar_perm(x, nb, wt, nsim = 499, alternative = "two.sided", ...)

Arguments

x

A numeric vector.

nb

a neighbor list object for example as created by st_contiguity().

wt

a weights list as created by st_weights().

alternative

default "two.sided". Should be one of "greater", "less", or "two.sided" to specify the alternative hypothesis.

...

methods passed to spdep::localG() or spdep::localG_perm()

nsim

The number of simulations to run.

Value

a data.frame with columns:

  • gi: the observed statistic

  • e_gi: the permutation sample mean

  • var_gi: the permutation sample variance

  • p_value: the p-value using sample mean and standard deviation

  • p_folded_sim: p-value based on the implementation of Pysal which always assumes a two-sided test taking the minimum possible p-value

  • skewness: sample skewness

  • kurtosis: sample kurtosis

Examples

nb <- st_contiguity(guerry)
wt <- st_weights(nb)
x <- guerry$crime_pers

res <- local_gstar_perm(x, nb, wt)
head(res)
#>     gi_star       e_gi       var_gi    p_value      p_sim p_folded_sim skewness
#> 1  1.342359 0.01281212 2.828987e-06  0.8669055 0.38599380        0.408    0.204
#> 2  2.595578 0.01231754 2.534491e-06  2.1922882 0.02835870        0.036    0.018
#> 3  2.388872 0.01226355 2.355173e-06  2.0995950 0.03576448        0.044    0.022
#> 4 -1.848187 0.01098208 2.788616e-06 -1.5970973 0.11024403        0.120    0.060
#> 5 -1.209736 0.01146742 3.231416e-06 -1.2477284 0.21213055        0.212    0.106
#> 6 -2.034142 0.01097455 1.880792e-06 -1.5710781 0.11616450        0.120    0.060
#>      kurtosis
#> 1  0.11601646
#> 2  0.13538275
#> 3  0.07291573
#> 4 -0.05713113
#> 5  0.13602702
#> 6  0.05456544

res <- local_gstar(x, nb, wt)
head(res)
#> [1]  1.342359  2.595578  2.388872 -1.848187 -1.209736 -2.034142