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Hi Dr. Ribeire,<br>
<br>
This is very helpful, thank you. I was assuming that my code did split
the nugget into measurement error and micro-scale variation when I
specified in the krige.control "micro=myfit$nugget/2" is this not
correct? This, I thought, splits the nugget in half. I also noticed
that when I do this, the kriging variance seems odd with a lot of zeros
or very low numbers do you know why?<br>
<br>
I don't suppose you can direct me to some example code that explains
how to compute the measurement error using locations as "blocks" and
subtracting from the nugget. I don't see that mentioned in your book
(the book is very useful by the way).<br>
<br>
Zev<br>
<br>
<br>
Paulo Justiniano Ribeiro Jr wrote:
<blockquote
cite="mid:Pine.LNX.4.58.0710301859310.20381@talisker.c3sl.ufpr.br"
type="cite">
<pre wrap="">Dear Zev
The warning is really just a warning and not an error...
the point is you may need some data manipulation in order to run the
analysis you anty.
Firts of all the fact you have duplicated information in (some) locations
may give you the opportunity to split you negget parameter estimate in
measurement error and micro-scale variation.
One possibility to compute the former using the duplicated data (locations
as "blocks" and subtract this from the nugget. The difference givesyouy
the latter.
You can them use thei information when kriging with krige.conv()
hope this helps, otherwise contact me again for further details
best
Paulo Justiniano Ribeiro Jr
LEG (Laboratório de Estatística e Geoinformação)
Universidade Federal do Paraná
Caixa Postal 19.081
CEP 81.531-990
Curitiba, PR - Brasil
Tel: (+55) 41 3361 3573
Fax: (+55) 41 3361 3141
e-mail: paulojus AT ufpr br
<a class="moz-txt-link-freetext" href="http://www.leg.ufpr.br/~paulojus">http://www.leg.ufpr.br/~paulojus</a>
On Tue, 30 Oct 2007, Zev Ross wrote:
</pre>
<blockquote type="cite">
<pre wrap="">Hi All,
At many monitoring locations we've taken two air quality samples. Rather than
simply average these values, I want to krige all the observations and
accommodate the different values at coincident locations by including
measurement error in the nugget.
When I run the code based on geoR, though, I get an error that the coincident
locations may "cause crashes in some matrices operations" and I'm wondering if
someone could shed light on the issue -- is this what you'd expect with
coincident locations? Is the code below incorrectly specified?
Thank you, Zev
# ----set up the modelling and validation samples as geodata
model.a<-as.geodata(samples.hull, coords.col=c("x", "y"),
data.col="no2.ppb",
covar.col=c("phase", "traffic) )
validation.a<-as.geodata(samples.val, coords.col=c("x", "y"),
data.col="no2.ppb",
covar.col=c("phase", "traffic) )
#-----use the modeling samples to estimate the variogram
myvario<-variog(model.a, option="bin",
breaks=seq(1,10000, by=300), maxdist=10000,
trend=~phase+traffic)
#----- fit the variogram
myfit<-variofit(myvario, ini.cov.pars=c(15, 1000),
cov.model="spherical")
#----- set kriging to include a trend AND split
#----- the nugget into micro and measurement
KC<-krige.control(type="ok", obj.model=myfit, micro=myfit$nugget/2,
trend.d=trend.spatial(~phase+traffic, model.a),
trend.l=trend.spatial(~phase+traffic, validation.a))
# ----krige
mykrige<-krige.conv(model.a,locations=validation.a$coords,
krige=KC, output=output.control(signal=F)
# here is the warning
krige.conv: model with covariates matrix provided by the user
krige.conv: Kriging performed using global neighbourhood
Warning message:
Two or more pairs of data at coincident (or very close) locations.
This may cause crashes in some matrices operations.
in: varcov.spatial(coords = coords, cov.model = cov.model, kappa = kappa,
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</pre>
</blockquote>
<pre wrap=""><!---->
</pre>
</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Zev Ross
ZevRoss Spatial Analysis
303 Fairmount Ave
Ithaca, NY 14850
607-277-0004 (phone)
866-877-3690 (fax, toll-free)
<a class="moz-txt-link-abbreviated" href="mailto:zev@zevross.com">zev@zevross.com</a></pre>
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