On Thu, 20 Nov 2008, Sam Veloz wrote:
I would like to run an anova on a set of raster variables imported from GRASS
into R but am confused about how R handles the raster data. So if I have a
model with a treatment with 2 levels, each raster is a binary file with cells
coded for each level of the treatment. I have 1 response raster layer that
corresponds spatially with the treatment layers. So let's say I have 5
rasters representing a different rep of the treatment how would I code this
in R? I started out trying this:
treatment<-readRAST6(c("rep1","rep2","rep3","rep4","rep5"),cat=TRUE)
response<-readRAST6("response",cat=FALSE)
test.aov<-aov(response~treatment)
The objects returned by readRAST6 are SpatialGridDataFrames. I think that
you may find that:
SGDF <- readRAST6(c("rep1", "rep2", "rep3", "rep4", "rep5", "response"),
cat=c(TRUE, TRUE, TRUE, TRUE, TRUE, FALSE))
test.aov <- aov(response ~ ., data=SGDF)
does the trick (the . inserts the remaining variables) - or safer:
test.aov <- aov(response ~ rep1 + rep2 + rep3 + rep4 + rep5, data=SGDF)
Untried.
By the way, do you need aov(), or would anova(lm()) do the same? I guess
the richer setting needs facilities in aov() that aren't visible here.
Hope this helps,
Roger
but I don't think this is right. Is it possible to do what I am trying? My
data is actually a bit more complicated than this but if I can clear this up
than I think I can do the rest on my own.
Thanks for your help,
Sam
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: [EMAIL PROTECTED]
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