Bivariate Local Join Count Statistics — local

The function to apply local Bivariate Join Count statistics

local_bijoincount(
  w,
  df,
  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 two selected variable. E.g. guerry[c("TopCrm", "InvCrm")]
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

Value

An instance of LISA-class

Examples

library(sf)
guerry_path <- system.file("extdata", "Guerry.shp", package = "rgeoda")
guerry <- st_read(guerry_path)
#> Reading layer `Guerry' from data source 
#>   `/Users/runner/work/_temp/Library/rgeoda/extdata/Guerry.shp' 
#>   using driver `ESRI Shapefile'
#> Simple feature collection with 85 features and 29 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 47680 ymin: 1703258 xmax: 1031401 ymax: 2677441
#> Projected CRS: NTF (Paris) / Lambert zone II
queen_w <- queen_weights(guerry)
guerry["InvCrm"] <-  1 - guerry[["TopCrm"]]
lisa <- local_bijoincount(queen_w, guerry[c("TopCrm", "InvCrm")])
clsts<- lisa_clusters(lisa)
clsts
#>  [1] 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> [39] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1
#> [77] 0 0 0 0 0 0 0 0 0