unimoran.test: Univariate Global Moran Statistic permutation test

In spdyn: Exploratory Space-Time Data Analysis

Univariate Global Moran Statistic permutation test

Description

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

Usage

unimoran.test(x,listw,CENT=mean,DESV=sd,nsim=999)

Arguments

x	A numeric vector.
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 unimoran.test function computes the value of the Univariate Global Moran Statistic. Morevoer, it generalizes the estimation of spatial autocorrelation, as this function allows to use alternative measures of central tendency and of dispersion. However, it should be noted that analytical results regarding the behavior of spatial autocorrelation are only available in the literature when the central tendency and the dispersion are measured as the mean and standard deviation, respectively.

Value

An object of class moranPerm:

sim_statistics	A vector with the values of the simulated univariate global moran statistic
statistic	Value of the univariate moran statistic as returned by the function unimoran
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, unimoran, bimoran.test

Examples

data(usinc)

require(spdep)

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

unimoran.test(usinc$X2009, listw=lw)

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