geary.mc | R Documentation |
A permutation test for Geary's C 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.
geary.mc(x, listw, nsim, zero.policy=attr(listw, "zero.policy"), alternative="greater",
spChk=NULL, adjust.n=TRUE, return_boot=FALSE)
x |
a numeric vector the same length as the neighbours list in listw |
listw |
a |
nsim |
number of permutations |
zero.policy |
default |
alternative |
a character string specifying the alternative hypothesis, must be one of "greater" (default), or "less"; this reversal corresponds to that on |
spChk |
should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use |
adjust.n |
default TRUE, if FALSE the number of observations is not adjusted for no-neighbour observations, if TRUE, the number of observations is adjusted |
return_boot |
return an object of class |
A list with class htest
and mc.sim
containing the following components:
statistic |
the value of the observed Geary's C. |
parameter |
the rank of the observed Geary's C. |
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 |
Roger Bivand Roger.Bivand@nhh.no
Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, p. 63-5.
geary
, geary.test
data(oldcol)
sim1 <- geary.mc(COL.OLD$CRIME, nb2listw(COL.nb, style="W"),
nsim=99, alternative="less")
sim1
mean(sim1$res)
var(sim1$res)
summary(sim1$res)
colold.lags <- nblag(COL.nb, 3)
sim2 <- geary.mc(COL.OLD$CRIME, nb2listw(colold.lags[[2]],
style="W"), nsim=99)
sim2
summary(sim2$res)
sim3 <- geary.mc(COL.OLD$CRIME, nb2listw(colold.lags[[3]],
style="W"), nsim=99)
sim3
summary(sim3$res)
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