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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     skewness
#> 1  0.8269073 0.01202468 4.708635e-06 0.40828962 0.384        0.192  0.108031563
#> 2  2.2675081 0.01190789 3.442762e-06 0.02335920 0.024        0.012 -0.022953469
#> 3  2.1065014 0.01195856 3.132039e-06 0.03516082 0.036        0.018  0.214384229
#> 4 -1.5578219 0.01193275 4.706590e-06 0.11927546 0.132        0.066 -0.064795417
#> 5 -1.2392682 0.01190442 5.660802e-06 0.21524620 0.224        0.112 -0.010932516
#> 6 -1.7438513 0.01198444 2.309388e-06 0.08118502 0.096        0.048 -0.008907957
#>      kurtosis
#> 1 -0.28223473
#> 2 -0.02445925
#> 3  0.08371985
#> 4 -0.21852436
#> 5 -0.06798521
#> 6 -0.27354822