local_multiquantilelisa: Multivariate Quantile LISA statistics

In lixun910/rgeoda: R Library for Spatial Data Analysis

Description

The function to apply multivariate quantile LISA statistics

Usage

local_multiquantilelisa(
  w,
  quantile_data,
  permutations = 999,
  significance_cutoff = 0.05,
  cpu_threads = 6,
  seed = 123456789
)

Arguments

w	An instance of Weight object
quantile_data	A list of [k, q, data] for more than one variable. Each variable will be set with: k, indicates the number of quantiles; q, indicates which quantile or interval used in local join count statistics; data, is a numeric array of selected variable
permutations	The number of permutations for the LISA computation
significance_cutoff	A cutoff value for significance p-values to filter not-significant clusters
cpu_threads	The number of cpu threads used for parallel LISA computation
seed	The seed for random number generator

Value

lisa_obj An instance of LISA (LocalSpatialAutocorrelation) object

Examples

guerry_path <- system.file("extdata", "Guerry.shp", package = "rgeoda")
guerry <- geoda_open(guerry_path)
queen_w <- queen_weights(guerry)
guerry_df <- as.data.frame(guerry) # use as data.frame
crm_prp <- guerry_df['Crm_prp'][,1]
lit <- guerry_df['Litercy'][,1]
quantiles <- list(list(4,1,crm_prp), list(4,1, lit))
lisa <- local_multiquantilelisa(queen_w, quantiles)
clsts <- lisa_clusters(lisa)
clsts

lixun910/rgeoda documentation built on March 19, 2021, 3:49 p.m.