local_bijoincount: Bivariate Local Join Count Statistics
In GeoDaCenter/rgeoda: R Library for Spatial Data Analysis

local_bijoincount

R Documentation

Bivariate Local Join Count Statistics

Description

The function to apply local Bivariate Join Count statistics

Usage

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)
queen_w <- queen_weights(guerry)
guerry["InvCrm"] <-  1 - guerry[["TopCrm"]]
lisa <- local_bijoincount(queen_w, guerry[c("TopCrm", "InvCrm")])
clsts<- lisa_clusters(lisa)
clsts

GeoDaCenter/rgeoda documentation built on Dec. 20, 2024, 11:18 p.m.