scores.listw {adespatial} | R Documentation |
Function to compute and manage Moran's Eigenvector Maps (MEM) of a listw object
Description
These functions compute MEM (i.e., eigenvectors of a doubly centered spatial weighting matrix). Corresponding eigenvalues are linearly related to Moran's index of spatial autocorrelation.
Usage
scores.listw(
listw,
wt = rep(1, length(listw$neighbours)),
MEM.autocor = c("non-null", "all", "positive", "negative"),
store.listw = FALSE
)
mem(
listw,
wt = rep(1, length(listw$neighbours)),
MEM.autocor = c("non-null", "all", "positive", "negative"),
store.listw = FALSE
)
orthobasis.listw(
listw,
wt = rep(1, length(listw$neighbours)),
MEM.autocor = c("non-null", "all", "positive", "negative"),
store.listw = FALSE
)
## S3 method for class 'orthobasisSp'
x[i, j, drop = TRUE]
Arguments
listw |
An object of the class |
wt |
A vector of weights. It is used to orthogonalize the eigenvectors. It could be useful if MEM are used in weighted regression or canonical correspondence analysis |
MEM.autocor |
A string indicating if all MEMs must be returned or only
those corresponding to non-null, positive or negative autocorrelation. The
difference between options |
store.listw |
A logical indicating if the spatial weighting matrix
should be stored in the attribute |
x |
An object of class |
i , j |
Elements to extract (integer or empty): index of rows (i) and columns (j). |
drop |
A logical. If TRUE, object containing only one colum is converted in vector |
Details
Testing the nullity of eigenvalues is based on E(i)/E(1) where E(i) is i-th eigenvalue and E(1) is the maximum absolute value of eigenvalues
Value
An object of class orthobasisSp
, subclass orthobasis
.
The MEMs are stored as a data.frame
. It contains several attributes
(see ?attributes
) including:
-
values
: The associated eigenvalues. -
listw
: The associated spatial weighting matrix (ifstore.listw = TRUE
).
Author(s)
Stéphane Dray stephane.dray@univ-lyon1.fr
References
Dray, S., Legendre, P., and Peres-Neto, P. R. (2006). Spatial modeling: a comprehensive framework for principal coordinate analysis of neighbor matrices (PCNM). Ecological Modelling 196, 483–493.
Griffith D. A. (1996) Spatial autocorrelation and eigenfunctions of the geographic weights matrix accompanying geo-referenced data. Canadian Geographer 40, 351–367.
See Also
Examples
if(require("ade4", quietly = TRUE) & require("spdep", quietly = TRUE)){
data(oribatid)
nbtri <- tri2nb(as.matrix(oribatid$xy))
sc.tri <- scores.listw(nb2listw(nbtri, style = "B"))
summary(sc.tri)
}
if(require("adegraphics", quietly = TRUE)){
s.value(oribatid$xy,sc.tri[,1:9])
plot(sc.tri[,1:6], oribatid$xy, pSp.cex = 5, pSp.alpha = 0.5, pbackground.col = 'lightblue')
}