On Sat, 23 Oct 2021, Gabriel Cotlier wrote:
Hello,
I would like to estimate the pseudo p-value of Moran's I from raster
data
layer, by converting it to polygon data in order to be able to directly
use
the function spdep::mc.moran() and getting in one step not only value
of
Moran'sI but its statistical significance without using other
simulations
but only that in the funcion spdep::mc.moran() as an alternative I have
used the code below. However, since with the initial version of the
code I
got several errors such as :
Error in moran. mc(My_raster, lw.l, 999) : r is not a numeric vector
So I converted "r" to a vector using as.vector() in :
M <- moran.mc(as.vector(r), lw.l, 999)
First, if you have the spatial weights object lw.l, spdep::moran.test(),
using analytical rather than bootstrap inference, is almost certainly
more
efficient, and yields almost always the same outcome with
randomisation=TRUE.
However then appeared another the error:
Error in na.fail.default(x) : missing values in object
Please see the na.action= argument to moran.mc() and moran.test(); the
default is na.fail, but can be na.exclude, which then also subsets the
listw spatial weights object. You can also subset l before creating the
neighbour object:
library(raster)
library(spdep)
r <- raster(nrows=10, ncols=10)
values(r) <- c(1:(ncell(r)-1), NA)
l <- rasterToPolygons(r, na.rm=TRUE) # note that this subsets by default
dim(l) # [1] 99 1
nb.l <- poly2nb(l, queen=FALSE)
nb.l # here no no-neighbour observations, no need for zero.policy=
lw.l <- nb2listw(nb.l, style="W")
moran.test(l$layer, lw.l) # default randomisation=TRUE
Finally these errors disappeared with the following version of the
code--
see below -- the version of the code below runs OK--unless for the
input
raster I have used-- with no more errors or problems.
Because rasterToPolygons() removes NA observations by default.
Hope this clarifies,
Roger
Therefore my question is : if instead of using arguments of the
function
spdep::mc.moran() such as na.action = na.omit or other --which I have
tried
and could not make work-- is it a valid way to solve the above errors
in
the way as presented in the code below?
I would appreciate it a lot if there is a possibility of knowing what
could
be wrong in the code below?
I suspect it could be possible the problem is related to the way in
which
the raster data layer is converted to polygon data im the code to be
input to the function spdep::mc.moran() , but will appreciate any
guidance
and assistance in the issue to get working in the correct manner.
Thanks a lot.
Kind regards,
################### Estimate of Moran's I and its p-value from a raster
layer ##################################
library(raster)
library(spdep)
library(easycsv)
rm(list = ls())
r<- raster(file.choose())
l <- rasterToPolygons(r)
nb.l <- poly2nb(l, queen=FALSE)
lw.l <- nb2listw(nb.l, style="W",zero.policy=TRUE)
v<-r[!is.na(r)]
M <- moran.mc((v), lw.l, 999, zero.policy=TRUE)
M
plot(M, main=sprintf("Original, Moran's I (p = %0.3f)", M$p.value),
xlab="Monte-Carlo Simulation of Moran I", sub =NA, cex.lab=1.5,
cex.axis=1.5, cex.main=1.5, cex.sub=1.5)
abline(v=M$statistic, col="red", lw=2)
dev.off()
################################################################################################
--
Roger Bivand
Emeritus Professor
Department of Economics, Norwegian School of Economics,
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
e-mail: roger.biv...@nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
