Hello,

>Why do you think it is better done in another program? Keeping it in R
saves you from the exporting, which you say you are having trouble with.

I think it might be better for viewing capabilities. If I had columns of
residuals right next to each other I could spot differences amongst
locations. Right? If I can take the residual values and put them back into
my main data file I can then have the options to use grouping values that
exist there. (Like I asked here:
http://tolstoy.newcastle.edu.au/R/e5/help/08/09/2186.html)

>> Q2: How can I take the residuals and create an object(s) for further
<http://tolstoy.newcastle.edu.au/R/e5/help/08/09/2259.html#2265qlink2>*analysis.
*
**

>See ?residuals.

>Try the following:

>x <- sample(1:20, 100, replace=TRUE)
>y <- rnorm(100)
>fit.lm <- lm(y ~ x)
>plot(residuals(fit.lm))
>plot(x,residuals(fit.lm))


When I was thinking further analysis, for example, could I take the
residuals for all metrics in one extent and compare them to all residuals
for all metrics in another extent? Even though the were created with 16
different models?

In 'plot(residuals(fit.lm))' what is the index 'counting'?


Thank you kindly for you $0.25,

Cheers,

M Just

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