Date: Thu, 26 May 2011 18:50:50 +0200
From: Jens Oldeland<oldeland at gmx.de>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Combining spatial and temporal correlation
structures - possible?
Message-ID:<4DDE84EA.2050308 at gmx.de>
Content-Type: text/plain; charset=ISO-8859-15; format=flowed
Dear Mixed-Model SIG
I am trying to use serial and spatial correlation structures in a gamm
model.
g2<- gamm(sqrt(pp10M.day) ~
s(tempsurf, bs="cr"),
data=data,
random= list(Station= ~1),
correlation=corARMA(form = ~ 1|Station, p =2,q=1),
family=gaussian,
control=lmc)
how do I put in my spatial correlation structure?
correlation=corExp(form = ~ Station,nugget=T)
I tried using correlation=list() but did not suceed. I did not find
anything in Zuur or Pinheiro& Bates etc.
would be glad if someone has an idea (or even says that it is not possible)
best,
Jens
------------------------------
Message: 5
Date: Thu, 26 May 2011 14:00:48 -0400
From: Ben Bolker<bbolker at gmail.com>
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Combining spatial and temporal correlation
structures - possible?
Message-ID:<4DDE9550.1000507 at gmail.com>
Content-Type: text/plain; charset=ISO-8859-1
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On 05/26/2011 12:50 PM, Jens Oldeland wrote:
Dear Mixed-Model SIG
I am trying to use serial and spatial correlation structures in a gamm
model.
g2<- gamm(sqrt(pp10M.day) ~
s(tempsurf, bs="cr"),
data=data,
random= list(Station= ~1),
correlation=corARMA(form = ~ 1|Station, p =2,q=1),
family=gaussian,
control=lmc)
how do I put in my spatial correlation structure?
correlation=corExp(form = ~ Station,nugget=T)
I tried using correlation=list() but did not suceed. I did not find
anything in Zuur or Pinheiro& Bates etc.
would be glad if someone has an idea (or even says that it is not possible)
I won't say it's impossible, but it's probably pretty tricky.
Spatio-temporal correlation structures are a research frontier (in my
opinoin at least). Separable correlation structures are easier than
non-separable ones (library("sos"); findFn("{spatio-temporal
correlation}") finds the ramps package ...
I think you'd probably have to build your own corClass. If you do
decide to go this route, I would strongly recommend looking at some
simple examples in packages *outside* of nlme -- e.g. the ape package --
findFn("corClasses") is a good start.
However, my recommendation would be to try to model the spatial
correlation via a spatial GAM (see examples in Simon Wood's book), and
leave the correlation stuff for the temporal component.
I'd be happy to hear other ideas.
Ben Bolker