On Mon, 24 Jul 2017, Rafael Pereira wrote:
Hi all,
I would like to ask whether some you conducted bi-variate spatial
correlation in R.
I know the bi-variate Moran's I is not implemented in the spdep library.
I left a question on SO but also wanted to hear if anyone if the mainlist
have come across this.
https://stackoverflow.com/questions/45177590/map-of-bivariate-spatial-correlation-in-r-bivariate-lisa
I also know Roger Bivand has implemented the L index proposed by Lee (2001)
in spdep, but I'm not I'm not sure whether the L local correlation
coefficients can be interpreted the same way as the local Moran's I
coefficients. I couldn't find any reference commenting on this issue. I
would very much appreciate your thoughts this.
In the SO question, and in the follow-up, your presumably throw-away
example makes fundamental mistakes. The code in spdep by Virgilio
Gómez-Rubio is for uni- and bivariate L, and produces point values of
local L. This isn't the main problem, which is rather that you are not
taking account of the underlying population counts, nor shrinking any
estimates of significance to accommodate population sizes. Population
sizes vary from 0 to 11858, with the lower quartile at 3164 and upper
5698: plot(ecdf(oregon.tract$pop2000)). Should you be comparing rates in
stead? These are also compositional variables (sum to pop2000, or 1 if
rates) with the other missing components. You would probably be better
served by tools examining spatial segregation, such as for example the seg
package.
The 0 count populations cause problems for an unofficial alternative, the
black/white ratio:
oregon.tract1 <- oregon.tract[oregon.tract$white > 0,]
oregon.tract1$rat <- oregon.tract1$black/oregon.tract1$white
nb <- poly2nb(oregon.tract1)
lw <- nb2listw(nb)
which should still be adjusted by weighting:
lm0 <- lm(rat ~ 1, weights=pop2000, data=oregon.tract1)
I'm not advising this, but running localmoran.sad on this model output
yields SAD p-values < 0.05 after FDR correction only in contiguous tracts
on the Washington state line in Portland between the Columbia and
Williamette rivers. So do look at the variables you are using before
rushing into things.
Hope this clarifies,
Roger
best,
Rafael HM Pereira
http://urbandemographics.blogspot.com
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Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: roger.biv...@nhh.no
Editor-in-Chief of The R Journal, https://journal.r-project.org/index.html
http://orcid.org/0000-0003-2392-6140
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