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<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'>Hi, <br>
<br>
Im using geoR and I'm trying to do some predictions, based on an external trend,
using ordinary kriging.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'>However, I seem to be getting some strange results
from my kriging, which I think must have something to do with a problem with my
prediction points. <br>
<br>
I have my geodata object (called nicola), my prediction points (predpoints,
imported from a csv containing only the x and y coordinated of the prediction
locations) and my covariate data at each of the prediction points (covars,
imported from a csv containing the x and y coordinates of the prediction
locations, plus the values of the two covariates I want to use at each of the
prediction locations). <br>
<br>
>predpoints<-read.csv(file="C:\\Documents and Settings\\s9901315\\My
<br>
+ Documents\\Uni\\Data\\Work\\Case control study\\Full study area\\R\\Files for
analysis\\Prediction <br>
+ points\\predpoints.csv", header=FALSE, sep=",") <br>
<br>
>covars<-read.csv(file="C:\\Documents and Settings\\s9901315\\My <br>
+ Documents\\Uni\\Data\\Work\\Case control study\\Full study area\\R\\Files for
analysis\\Covariate <br>
+ data\\covars.csv", header=TRUE, sep=",") <br>
<br>
The final model is defined using "OTUBOIDIST" and "LSTPHAN"
as external covariates: <br>
<br>
>mlx2<-likfit(nicola, cov.model="mat", kap=0.5, ini=c(0.6, 20),
nug=0.3, trend=~OTUBOIDIST + <br>
+ LSTPHAN) <br>
<br>
and then I carry out the kriging using the model "mlx2", prediction
points "predpoints", and covariate data "covars" : <br>
<br>
>kcontrol<-krige.control(obj.m=mlx2, type.krige="ok",
trend.d=~OTUBOIDIST + LSTPHAN, <br>
+ trend.l=~covars$otuboidist + covars$lstphan) <br>
<br>
>krige<-krige.conv(nicola, loc=predpoints, krige=kcontrol) <br>
<br>
Then I view it using the image function: <br>
<br>
>image(krige, col=gray(seq(1, 0.2, l=100))) <br>
<br>
The resulting image is clearly wrong with a regular stepped line appearing
diagonally across the image, and the predicted values do not coincide with the
actual observed data at all. I've included the predicted data image, as
well as the predicted image overlaid with the data points.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'>Can anyone give me any pointers of why this may be
going wrong? I've tried the same thing many times having changed
everything I can think of that might be causing the problem. <br>
<br>
Thanks in advance, <o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'>Nicola<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN-GB
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN-GB style='font-size:
10.0pt;font-family:Arial'><img width=483 height=429 id="_x0000_i1025"
src="cid:image001.jpg@01C909B7.E339C910"><img width=477 height=433
id="_x0000_i1031" src="cid:image002.jpg@01C909B7.E339C910"><o:p></o:p></span></font></p>
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