[R] Plotting lm() attributes

[Tony Plate]

I believe this is the sort of things that the functions resid() and 
predict(), in conjunction with na.exclude, are designed for.  E.g.:

 > data <- data.frame(x=c(1:5), y=c(1,3,2,NA,4))
 > m <- lm(y~x, data=data, na.action=na.exclude)
 > predict(m)
        1        2        3        4        5
1.400000 2.028571 2.657143       NA 3.914286
 > resid(m)
           1           2           3           4           5
-0.40000000  0.97142857 -0.65714286          NA  0.08571429
 >

Note that NA's are not reintroduced if na.action=na.omit, which is the 
default (unless you have options("na.action") set otherwise).  Also, note 
that this technique produces a NA fitted value where a non-NA one could be 
produced (use predict(m, newdata=data) to get those values.)

hope this helps,

Tony Plate

At Thursday 11:40 AM 11/13/2003 +1300, Murray Jorgensen wrote:
>Suppose you fit a linear model
>
> > model.1 ~ lm(v1 ~ ..., data=myframe)
>
>and v2 is some other column of myframe typically not in the model. You 
>will often want to try
>
> > plot(v2, model.1$residuals)
>
>but this will fail if there are NAs in the response v1 as 
>model.1$residuals has length equal to the number of nonmissing values 
>in  v1. I suppose
>
> > plot(v2[!is.na(v1)], model.1$residuals)
>
>does the job, but it seems irritating that model.1$residuals, does not 
>have length agreeing with the number of rows in the data frame. It would 
>be even more irritating for model.1$fitted.values, where the removed 
>elements would often have nonmissing values.
>
>Murray
>
>--
>Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
>Department of Statistics, University of Waikato, Hamilton, New Zealand
>Email: maj at waikato.ac.nz                                Fax 7 838 4155
>Phone  +64 7 838 4773 wk    +64 7 849 6486 home    Mobile 021 1395 862
>
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Tony Plate   tplate at acm.org