# residual.plots

From HH v3.1-8
by Richard Heiberger

##### Residual plots for a linear model.

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").

- Keywords
- hplot, regression

##### Usage

```
residual.plots(lm.object, X=dft$x,
layout=c(dim(X)[2],1),
par.strip.text=list(cex=.8),
scales.cex=.6,
na.action=na.pass,
y.relation="free",
...)
```

##### Arguments

- lm.object
- An object inheriting from
`"lm"`

. It may be necessary for the`lm.object`

to be constructed with arguments`x=TRUE, y=TRUE`

. - X
- The x matrix of predictor variables used in the linear model
`lm.object`

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

argument forwarded to the scales argument of`xyplot`

.- na.action
- A function to filter missing data. See
`lm`

. - y.relation
- See
`relation`

in the discussion of the`scales`

argument in#ifndef S-Plus`xyplot`

. #endif #ifdef S-Plus`trellis`

- ...
- Other arguments for
`xysplom`

or`xyplot`

.

##### 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.

##### References

Heiberger, Richard M. and Holland, Burt (2004b).
*Statistical Analysis and Data Display: An Intermediate Course
with Examples in S-Plus, R, and SAS*.
Springer Texts in Statistics. Springer.
ISBN 0-387-40270-5.

##### See Also

##### Examples

```
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 S-Plus 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
```

*Documentation reproduced from package HH, version 3.1-8, License: GPL (>= 2)*

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