Greg,
Thanks for the pseudocode and cbind suggestions I think these should be
quite helpful. What package is the function 'view' in? As for exporting
elsewhere, basically I would to have the values of residuals saved in a
spreadsheet in addition to any visualizations created within R.

Thanks,
M Just

On Tue, Sep 23, 2008 at 3:26 PM, Greg Snow <Greg.Snow@imail.org> wrote:

> You can do things like this pseudocode:
>
> > fit1 <- lm( y ~ x1, data=mydata )
> > fit2 <- lm( y ~ x2, data=mydata )
> > fit3 <- lm( y ~ x1*x2, data=mydata )
> ...
>
> > mydata$r1 <- resid(fit1)
> > mydata$r2 <- resid(fit2)
> > mydata$r3 <- resid(fit3)
>
> Or
>
> > mydata <- cbind(mydata, r1=resid(fit1), r2=resid(fit2), ...
>
> To view the data in a spreadsheet like table:
>
> > View(mydata)
>
> And scroll over to the r columns, using indexing or the subset function can
> reorder the columns to make this easier.
>
> A simple plot:
>
> > pairs( mydata[ , paste('r',1:10, sep='')], col=c('red','green','blue')[
> mydata$g1 ],
> + panel=panel.smooth )
>
> Or there are various other ways to explore the data within R.  If you
> really feel the need to use another tool, do like the above, then use
> write.table to export it to a csv file or paste it to a spreadsheet.   There
> is also the rggobi package which will automate the exporting to the ggobi
> program which allows a lot more visualization options.
>
> Hope this helps,
>
>
> --
> Gregory (Greg) L. Snow Ph.D.
> Statistical Data Center
> Intermountain Healthcare
> greg.snow@imail.org
> 801.408.8111
>
>
> > -----Original Message-----
> > From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-
> > project.org] On Behalf Of Michael Just
> > Sent: Tuesday, September 23, 2008 2:06 PM
> > To: r-help@r-project.org
> > Cc: NordlDJ@dshs.wa.gov
> > Subject: Re: [R] Options for viewing / using results from lm
> >
> > 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
> >
> >         [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>

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