global_moran_bv: Compute the Global Bivariate Moran's I

In sfdep: Spatial Dependence for Simple Features

Compute the Global Bivariate Moran's I

Description

Given two continuous numeric variables, calculate the bivariate Moran's I. See details for more.

Usage

global_moran_bv(x, y, nb, wt, nsim = 99, scale = TRUE)

Arguments

x	a numeric vector of same length as y.
y	a numeric vector of same length as x.
nb	a neighbor list object for example as created by st_contiguity().
wt	a weights list as created by st_weights().
nsim	the number of simulations to run.
scale	default TRUE.

Details

The Global Bivariate Moran is defined as

I_B = \frac{\Sigma_i(\Sigma_j{w_{ij}y_j\times x_i})}{\Sigma_i{x_i^2}}

It is important to note that this is a measure of autocorrelation of X with the spatial lag of Y. As such, the resultant measure may overestimate the amount of spatial autocorrelation which may be a product of the inherent correlation of X and Y.

Value

an object of class boot

References

Global Spatial Autocorrelation (2): Bivariate, Differential and EB Rate Moran Scatter Plot, Luc Anselin

See Also

Other global_moran: global_moran(), global_moran_perm(), global_moran_test(), local_moran_bv()

Examples

x <- guerry_nb$crime_pers
y <- guerry_nb$wealth
nb <- guerry_nb$nb
wt <- guerry_nb$wt
global_moran_bv(x, y, nb, wt)

sfdep documentation built on Sept. 13, 2024, 5:07 p.m.