Plots to assess the goodness of fit for the linear model objects

```
lmplot2(
x,
which = 1:5,
caption = c("Residuals vs Fitted", "Normal Q-Q plot",
"Scale-Location plot", "Cook's distance plot"),
panel = panel.smooth,
sub.caption = deparse(x$call),
main = "",
ask = interactive() && nb.fig < length(which)
&& .Device != "postscript",
...,
id.n = 3,
labels.id = names(residuals(x)),
cex.id = 0.75,
band=TRUE,
rug=TRUE,
width=1/10,
max.n=5000
)
```

x

lm object

which

Numerical values between 1 and 5, indicating which plots to be shown. The codes are:

- 1
Fitted vs residuals

- 2
Normal Q-Q

- 3
Scale-Location

- 4
Cook's distance

- 5
Residuals vs. predictor

caption

Caption for each type of plot

panel

function to draw on the existing plot

sub.caption

SubCaption for the plots

main

Main title of the plot

ask

whether interactive graphics

…

parameters passed to `lmplot2`

.

id.n

integer value, less than or equal to residuals of lm object

labels.id

Names of the residuals of the lm object

cex.id

Parameter to control the height of text stringsx

band

logical vector indicating whether bandplot should also be plotted

rug

logical vector indicating whether rug should be added to the existing plot

width

Fraction of the data to use for plot smooths

max.n

Maximum number of points to display in plots

# NOT RUN { ctl <- rnorm(100, 4) trt <- rnorm(100, 4.5) group <- gl(2,100,200, labels=c("Ctl","Trt")) weight <- c(ctl, trt) wt.err <- rnorm(length(weight), mean=weight, sd=1/2) x <- lm(weight ~ group + wt.err) lmplot2(x) lmplot2(x, which=1, width=1/3) lmplot2(x, which=1:3, width=1/3) # }