bimoran.test: Bivariate Global Moran Statistic permutation test

In spdyn: Exploratory Space-Time Data Analysis

Bivariate Global Moran Statistic permutation test

Description

This function computes a conditional permutation test for the Bivariate Global Moran Statistic.

Usage

bimoran.test(x,y=NULL,listw,CENT=mean,DESV=sd,nsim=999)

Arguments

x	Either a numeric vector or a numeric matrix with two columns. If x has more than two columns, only the first two columns will be used, and the second column will be spatially lagged.
y	A numeric vector. This is the variable to be spatially lagged. If x is a numeric matrix, there is no need to supply this argument.
listw	A list of spatial weights as provided by spdep::nb2listw
CENT	Central tendency statistic used to compute the Moran Statistic. Defaults to mean
DESV	Dispersion statistic. Defaults to sd
nsim	Number of permutations or simulations.

Details

The bimoran.test implements a conditional permutation test to asses the statistical significance of the Bivariate Global Moran Statistic.

Value

An object of class moranPerm:

sim_statistics	A vector with the values of the simulated bivariate global moran statistic
statistic	Value of the bivariate moran statistic as returned by the function bimoran
pvalue	Pseudo p-value returned by the permutation test

Author(s)

Osmar Leandro Loaiza Quintero

References

Anselin, Luc (1995). Local Indicators of Spatial Association. Geographical Analysis

See Also

bilisa.perm, bimoran, unimoran.test

Examples

data(usinc)

require(spdep)

lw<-nb2listw(
		poly2nb(usinc,queen=TRUE),style='W'
	)

bimoran.test(x=usinc$X2007, y=usinc$X2009, listw=lw)

spdyn documentation built on Oct. 28, 2024, 3 p.m.