moran.mc {spdep}R Documentation

Permutation test for Moran's I statistic

Description

A permutation test for Moran's I statistic calculated by using nsim random permutations of x for the given spatial weighting scheme, to establish the rank of the observed statistic in relation to the nsim simulated values.

Usage

moran.mc(x, listw, nsim, zero.policy=FALSE, alternative="greater", spChk=NULL)

Arguments

x a numeric vector the same length as the neighbours list in listw
listw a listw object created for example by nb2listw
nsim number of permutations
zero.policy if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
alternative a character string specifying the alternative hypothesis, must be one of greater (default), less or two.sided.
spChk should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use get.spChkOption()

Value

A list with class htest and mc.sim containing the following components:

statistic the value of the observed Moran's I.
parameter the rank of the observed Moran's I.
p.value the pseudo p-value of the test.
alternative a character string describing the alternative hypothesis.
method a character string giving the method used.
data.name a character string giving the name(s) of the data, and the number of simulations.
res nsim simulated values of statistic, final value is observed statistic

Author(s)

Roger Bivand Roger.Bivand@nhh.no

References

Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, p. 63-5.

See Also

moran, moran.test

Examples

data(oldcol)
sim1 <- moran.mc(spNamedVec("CRIME", COL.OLD), nb2listw(COL.nb, style="W"),
 nsim=99)
mean(sim1$res)
var(sim1$res)
summary(sim1$res)
colold.lags <- nblag(COL.nb, 3)
sim2 <- moran.mc(spNamedVec("CRIME", COL.OLD), nb2listw(colold.lags[[2]],
 style="W"), nsim=99)
summary(sim2$res)
sim3 <- moran.mc(spNamedVec("CRIME", COL.OLD), nb2listw(colold.lags[[3]],
 style="W"), nsim=99)
summary(sim3$res)

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