PermutationGi: Permutation based Getis-Ord Gi or Gi* statistics for spatial...

In spots: Spatial Component Analysis

Permutation based Getis-Ord Gi or Gi* statistics for spatial hots pot analysis

Description

Calculate permutation based p-value for Getis-Ord Gi or Gi* statistics.

Usage

PermutationGi(
  x,
  W,
  gstar = TRUE,
  n = 999,
  seed = 1,
  alternative = c("two.sided", "less", "greater"),
  p.adjust.method = "BH",
  return.permutation = FALSE,
  condition = 0
)

Arguments

x	A numerical vector.
W	A weight matrix across all observations, i.e inverse of a pairwise distance matrix.
gstar	Whether to calculate the Gi* statistics, default is TRUE.
n	The number of permutations to be conducted, set to 999 by default.
seed	Random seed used. Default is 1.
alternative	Alternative hypothesis used, default is two.sided.
p.adjust.method	Method used for multiple comparisons correction, default is BH. See p.adjust.
return.permutation	Return permutations. Default is FALSE.
condition	Value under null hypothesis to compare with, default is 0.

Value

A list containing the following:

• Gi, Gi or Gi* statistics.

• p.val, permutation based p-value.

• p.adj, adjusted p-values.

• return.permutation, permutation used if returned.

• params, parameters used to calculate local Moran's I.

Examples

{
data.use <- quakes[1:100,]
W <- 1/as.matrix(dist(data.use[,1:2]))
diag(W) <- 0
res <- PermutationGi(data.use[,3], W)
}

spots documentation built on May 3, 2022, 5:06 p.m.