[R-sig-Geo] question on raster Moran's I statistical significance

[Gabriel Cotlier]

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 using 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 using 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

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