question on raster Moran's I statistical significance

nb.l

lw.l <- nb2listw(nb.l, style="W",zero.policy = TRUE)

moran.test(l$dta, lw.l,zero.policy = TRUE) # default randomisation=TRUE

On Mon, 25 Oct 2021, Gabriel Cotlier wrote:

Hello,

I have tried the code for most of the dataset but only few make the
same error:

nb.l

Neighbour list object:
Number of regions: 975434
Number of nonzero links: 3869290
Percentage nonzero weights: 0.0004066638
Average number of links: 3.966737
79 regions with no links:
3206 34632 47267 65155 81013 90934 91361 91427 98318
98765 100054 100472 100884 100896 102508 102514 105207
105937 106630 106965 114449 115479 122329 123614 126880
128631 314459 350405 381283 397379 401275 412489 420698
426384 428632 429752 432058 433230 440631 451195 451196
452270 464327 467009 503242 504459 507625 510412 517865
517916 524413 526766 535269 537320 537712 544576 549519
551629 553413 565169 566421 567703 567791 568587 579209
585464 625809 642179 648122 651096 652581 654065 708908
777500 845322 846238 847153 848065 866391

lw.l <- nb2listw(nb.l, style="W")

Error in nb2listw(nb.l, style = "W") : Empty neighbour sets found

Could it be something related to the input data layer?

Yes. Please also look at the output of spdep::n.comp.nb() if it works for
a dataset this large, see ?n.comp.nb and examine the nc component (number
of subgraphs). The singleton graphs have no neighbours, but there may be
other subgraphs, you find their sizes by table(table(<comp.id
component>)). This may well have come from the na.rm=TRUE in
rasterToPolygons(), but is unavoidable. Maybe see also:
https://keen-swartz-3146c4.netlify.app/area.html#
and expand all code (button at top right) and search for n.comp.nc.

Since you have singleton observations, zero.policy=TRUE is your only
option unless you further subset by omitting all the observations for
which card(nb.l) == 0L - since they have no neighbours, they do not inform
the spatial process.

Roger

How could it be possible to avoid this error for running the code?

Thanks a lot for your guidance and help.

Kind regards,
Gabriel Cotlier


On Mon, Oct 25, 2021 at 12:21 PM Gabriel Cotlier <gabiklm01 at gmail.com>
wrote:

Thank you very much for your response.
Yes indeed it clarifies and helps a lot.
Kind regards,
Gabriel Cotlier

On Mon, Oct 25, 2021 at 12:00 PM Roger Bivand <Roger.Bivand at nhh.no>

wrote:

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.Bivand at nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en

--
Gabriel Cotlier, PhD
Haifa Research Center for Theoretical Physics and Astrophysics (HCTPA)
University of Haifa
Israel

--
Roger Bivand
Emeritus Professor
Department of Economics, Norwegian School of Economics,
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
e-mail: Roger.Bivand at nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en