Residual plots for a linear model.
Description
Residual plots for a linear model. Four sets of plots are produced: (1) response against each of the predictor variables, (2) residuals against each of the predictor variables, (3) partial residuals for each predictor against that predictor ("partial residuals plots", and (4) partial residuals against the residuals of each predictor regressed on the other predictors ("added variable plots").
Usage
1 2 3 4 5 6 7 
Arguments
lm.object 
An object inheriting from 
X 
The x matrix of predictor variables used in the linear model

layout, par.strip.text 
trellis or lattice arguments. 
scales.cex 

na.action 
A function to filter missing data. See 
y.relation 
See 
... 
Other arguments for 
Value
A list of four trellis objects, one for each of the four sets of
plots. The objects are named "y.X"
, "res.X"
"pres.X"
, "pres.Xj"
. The default "printing" of the
result will produce four pages of plots, one set per page. They are
often easier to read when all four sets appear as separate rows on one
page (this usually requires an oversize device), or two rows are
printed on each of two pages.
Author(s)
Richard M. Heiberger <rmh@temple.edu>
References
Heiberger, Richard M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in SPlus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0387402705.
See Also
residual.plots.lattice
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  if.R(s={
longley < data.frame(longley.x, Employed = longley.y)
},r={
data(longley)
})
longley.lm < lm( Employed ~ . , data=longley, x=TRUE, y=TRUE)
## 'x=TRUE, y=TRUE' are needed to pass the SPlus CMD check.
## They may be needed if residual.plots() is inside a nested set of
## function calls.
tmp < residual.plots(longley.lm)
## print two rows per page
print(tmp[[1]], position=c(0, 0.5, 1, 1.0), more=TRUE)
print(tmp[[2]], position=c(0, 0.0, 1, 0.5), more=FALSE)
print(tmp[[3]], position=c(0, 0.5, 1, 1.0), more=TRUE)
print(tmp[[4]], position=c(0, 0.0, 1, 0.5), more=FALSE)
## print as a single trellis object
ABCD < do.call(rbind, lapply(tmp, as.vector))
dimnames(ABCD)[[1]] < dimnames(tmp[[1]])[[1]]
ABCD
