Permutation based local Moran's I — PermutationLocalI • spots

Calculate permutation based p-value for local Moran's I.

PermutationLocalI(
  x,
  W,
  n = 999,
  seed = 1,
  alternative = c("two.sided", "less", "greater"),
  p.adjust.method = "BH",
  normalize = TRUE,
  scale = TRUE,
  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.
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.
normalize: Whether to normalize the weight matrix such that each row adds up to one. Default is TRUE.
scale: Whether to scale the data. Default is TRUE.
return.permutation: Return permutations. Default is FALSE.
condition: Value under null hypothesis to compare with, default is 0.

Value

A list containing the following:

Local.Morans.I, local Moran's I.
p.val, permutation based p-value.
p.adj, adjusted p-values.
scale.factor, number of observations.
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 <- PermutationLocalI(data.use[,3], W)
}