local_multiquantilelisa function

Multivariate Quantile LISA Statistics

The function to apply multivariate quantile LISA statistics

local_multiquantilelisa(
  w,
  df,
  k,
  q,
  permutations = 999,
  permutation_method = "complete",
  significance_cutoff = 0.05,
  cpu_threads = 6,
  seed = 123456789
)

Arguments

• w: An instance of Weight object
• df: A data frame with selected variables only. E.g. guerry[c("TopCrm", "TopWealth", "TopLit")]
• k: A vector of "k" values indicate the number of quantiles for each variable. Value range e.g. [1, 10]
• q: A vector of "q" values indicate which quantile or interval for each variable used in local join count statistics. Value stars from 1.
• permutations: (optional) The number of permutations for the LISA computation
• permutation_method: (optional) The permutation method used for the LISA computation. Options are ('complete', 'lookup'). Default is 'complete'.
• significance_cutoff: (optional) A cutoff value for significance p-values to filter not-significant clusters
• cpu_threads: (optional) The number of cpu threads used for parallel LISA computation
• seed: (optional) The seed for random number generator

Returns

An instance of LISA-class

Examples

library(sf)
guerry_path <- system.file("extdata", "Guerry.shp", package = "rgeoda")
guerry <- st_read(guerry_path)
queen_w <- queen_weights(guerry)
lisa <- local_multiquantilelisa(queen_w, guerry[c("Crm_prp", "Litercy")],
k=c(4,4), q=c(1,1))
clsts <- lisa_clusters(lisa)
clsts