PermutationLocalI: Permutation based local Moran's I

In spots: Spatial Component Analysis

Permutation based local Moran's I

Description

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

Usage

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)
}

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