Options for viewing / using results from lm
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 at imail.org 801.408.8111
-----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- project.org] On Behalf Of Michael Just Sent: Tuesday, September 23, 2008 2:06 PM To: r-help at r-project.org Cc: NordlDJ at 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
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