[R-sig-Geo] Specifying neighbourhood structure for Spatial Eigenvector Mapping (SEVM) using ME() in spdep
Roger Bivand
Roger.Bivand at nhh.no
Fri Sep 13 14:25:16 CEST 2013
You asked the same question yesterday (but simply added it to the original
thread from 2009). Do read the instructions for posting and the posting
guide. This is not a question concerned with the use of software, indeed,
had you used the software, you could have examined the questions you ask
empirically. Usually, no response to a posting results from a question
with little relevance, so repeating it is not a good idea at all.
You do not indicate having read anything, the original thread mentioned
Dormann et al. (2007) - are you aware of subsequent publications on using
PCNM/Moran eigenvectors/Spatial filtering, and if not, why not? There are
of course no theoretical reasons for not using different weighting
schemes; the schemes used are user choices, as you would realise if you
had taken time to study the literature. Have you read Borcard et al.
(2011):
http://www.springer.com/statistics/life+sciences,+medicine+%26+health/book/978-1-4419-7975-9
Section 7.4?
With regard to your questions, of course you can, but it is your judgement
as a researcher that should guide your choices, never advice from list
members - it is your responsibility entirely.
Roger
On Fri, 13 Sep 2013, Xochitl CORMON wrote:
> Dear list,
>
> I found a message asking same kind of things I am wondering. Unfortunately I
> dont find proper answers and thus would like to update the topic. Maybe
> Xingli could you share what your learn from the authors with us to the
> questions below?
>
> Regarding the weights, is it imperative for me to use (1-((x/4t)^2)? Can we
> just do an inverse weighting system like (1/x)? Can I also use weighted (C or
> W) instead of binary (B) weighting? Lastly, can I specify the threshold
> distance instead of using a spanning tree algorithm?
>
> Regards,
>
> Xo
>
> ###### Original message
> (SEVM) using ME() in spdep
> Xingli Giam Xingli Giam
> Jan 27, 2009 at 9:38 am
> Dear people of the R-sig-Geo list,
>
> I am very interested in the Spatial Eigenvector Mapping (SEVM) method in
> analysing my spatial data as described in your papers (Griffith and
> Peres-Neto
> 2006, Dormann et al. 2007).
>
> However I am rather new to spatial analysis and therefore have some questions
> regarding the script provided in the appendix of Dormann et al. 2007.
>
> Code
> nb1.0 <- dnearneigh(coordinates(snouter_sp), 0, 1.0)
>
> nb1.0_dists <- nbdists(nb1.0, coordinates(snouter_sp))
>
> nb1.0_sims <- lapply(nb1.0_dists, function(x) (1-((x/4)^2)) )
>
> ME.listw <- nb2listw(nb1.0, glist=nb1.0_sims, style="B")
>
> sevm1 <- ME(snouter1.1 ~ rain + djungle, data=snouter.df, family=gaussian,
>
> listw=ME.listw)
>
> # modify the arguments "family" according to your error distribution
>
> I hope someone who has experience in suing SEVM can give me a hand with some
> of
> the questions I have.
>
> Regarding the weights, is it imperative for me to use (1-((x/4t)^2)? Can we
> just do an inverse weighting system like (1/x)? Can I also use weighted (C or
> W) instead of binary (B) weighting in this line -ME.listw <- nb2listw(nb1.0,
> glist=nb1.0_sims, style="B")? Lastly, can I specify t, the threshold distance
> instead of using a spanning tree algorithm?
>
> Some background information about my data - it is in long-lat coordinates,
> and
> I have calculated great circle distances.
>
> And the code I was trying to use:
>
> nb <- dnearneigh(as.matrix(dat$x_long, dat$y_lat), 0, 4000, longlat=T)
> nb_dists <- nbdists(nb, as.matrix(dat$x_long, dat$y_lat))
> nb_sims <- lapply(nb_dists, function(x) (1/x))
> ME.listw <- nb2listw(nb, glist=nb_sims, style="W", zero.policy=T)
>
> sevm1 <- ME(lg.sp1 ~ lg.area, data=dat, family=gaussian, listw=ME.listw)
> lmlag1 <- lm(lg.sp1 ~ lg.area + fitted(sevm1), data=dat)
> moran<- moran.test(residuals(lmlag1), listw=ME.listw, na.action=na.omit,
> zero.policy=T)
> moran
>
>
> Thank you in advance for your help! Hope to hear from you soon!
>
> Many thanks,
> Xingli
> ######
>
>
--
Roger Bivand
Department of Economics, NHH Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
More information about the R-sig-Geo
mailing list