moranNP.randtest {adespatial} | R Documentation |
Function to compute positive and negative parts of Moran's index of spatial autocorrelation
Description
This function computes positive and negative parts of Moran's I statistic and
provide a testing procedure using random permutations. The functions compute
the Moran's eigenvector maps (MEM) and eigenvalues for the listw
object. If alter = "greater"
, the statistic 'I+' is computed as the
sum of the products between positive eigenvalues and squared correlations
between x
and associated MEMs. If alter = "less"
, the statistic
'I-' is computed as the sum of the products between negative eigenvalues and
squared correlations between x
and associated MEMs. If alter =
"two-sided"
, both statistics are computed.
Usage
moranNP.randtest(
x,
listw,
nrepet = 999,
alter = c("greater", "less", "two-sided"),
...
)
Arguments
x |
a |
listw |
an object of class |
nrepet |
an integer indicating the number of permutations used in the randomization procedure |
alter |
a character string specifying the alternative hypothesis, must be one of "greater" (default), "less" or "two-sided" |
... |
other arguments (e.g., |
Value
An object of class randtest
(for unilateral test) or
krandtest
(for bilateral test)
Author(s)
Stéphane Dray stephane.dray@univ-lyon1.fr
References
Dray, S. (2011). A new perspective about Moran's coefficient: spatial autocorrelation as a linear regression problem. Geographical Analysis, 43, 127-141.
See Also
Examples
if(require("ade4", quietly = TRUE) & require("spdep", quiet = TRUE)){
data(mafragh)
tests <- moranNP.randtest(mafragh$env[,1], nb2listw(mafragh$nb),
alter = "two-sided", p.adjust.method = "holm")
tests
moran.randtest(mafragh$env[,1], nb2listw(mafragh$nb))$obs
sum(tests$obs)
}