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Local G

Source: R/localG.R
local_g.Rd

Calculate the local Geary statistic for a given variable.

Usage

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

local_g_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

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

res <- local_g_perm(x, nb, wt)

head(res)
#>           gi       e_gi       var_gi    p_value      p_sim p_folded_sim
#> 1  0.8991367 0.01181669 5.294820e-06  0.8701837 0.38420001        0.424
#> 2  2.4455980 0.01191097 2.889082e-06  2.4734589 0.01338122        0.008
#> 3  2.1976551 0.01190228 2.679746e-06  2.3117279 0.02079268        0.036
#> 4 -1.5838690 0.01188818 4.847045e-06 -1.5148402 0.12981289        0.116
#> 5 -1.1902425 0.01187490 6.603139e-06 -1.1359518 0.25597672        0.252
#> 6 -1.6527255 0.01185289 2.372027e-06 -1.6352541 0.10199579        0.104
#>   skewness    kurtosis
#> 1    0.212  0.06130549
#> 2    0.004 -0.13947731
#> 3    0.018  0.21507002
#> 4    0.058  0.09450422
#> 5    0.126  0.22713868
#> 6    0.052  0.16068469