# ceresPlots

##### Ceres Plots

These functions draw Ceres plots for linear and generalized linear models.

- Keywords
- hplot, regression

##### Usage

```
ceresPlots(model, terms = ~., layout = NULL, ask, main,
...)
ceresPlot(model, ...)
## S3 method for class 'lm':
ceresPlot(model, variable,
id.method = list(abs(residuals(model, type="pearson")), "x"),
labels,
id.n = if(id.method[1]=="identify") Inf else 0,
id.cex=1, id.col=palette()[1],
line=TRUE, smooth=TRUE, span=.5, iter,
col=palette()[1], col.lines=palette()[-1],
xlab, ylab, pch=1, lwd=2,
grid=TRUE, ...)
## S3 method for class 'glm':
ceresPlot(model, ...)
```

##### Arguments

- model
- model object produced by
`lm`

or`glm`

. - terms
- A one-sided formula that specifies a subset of the predictors.
One component-plus-residual plot is drawn for each term. The default
`~.`

is to plot against all numeric predictors. For example, the specification`terms = ~ . - X3`

- layout
- If set to a value like
`c(1, 1)`

or`c(4, 3)`

, the layout of the graph will have this many rows and columns. If not set, the program will select an appropriate layout. If the number of graphs exceed nine, you must select the la - ask
- If
`TRUE`

, ask the user before drawing the next plot; if`FALSE`

, the default, don't ask. This is relevant only if not all the graphs can be drawn in one window. - main
- Overall title for any array of cerers plots; if missing a default is provided.
- ...
`ceresPlots`

passes these arguments to`ceresPlot`

.`ceresPlot`

passes them to`plot`

.- variable
- A quoted string giving the name of a variable for the horizontal axis
- id.method,labels,id.n,id.cex,id.col
- Arguments for the labelling of
points. The default is
`id.n=0`

for labeling no points. See`showLabels`

for details of these arguments. - line
`TRUE`

to plot least-squares line.- smooth
`TRUE`

to plot nonparametric-regression (lowess) line.- span
- span for lowess smoother.
- iter
- number of robustness iterations for nonparametric-regression smooth; defaults to 3 for a linear model and to 0 for a non-Gaussian glm.
- col
- color for points; the default is the first entry
in the current color palette (see
`palette`

and`par`

). - col.lines
- a list of at least two colors. The first color is used for the
ls line and the second color is used for the fitted lowess line. To use
the same color for both, use, for example,
`col.lines=c("red", "red")`

- xlab,ylab
- labels for the x and y axes, respectively. If not set appropriate labels are created by the function.
- pch
- plotting character for points; default is
`1`

(a circle, see`par`

). - lwd
- line width; default is
`2`

(see`par`

). - grid
- If TRUE, the default, a light-gray background grid is put on the graph

##### Details

Ceres plots are a generalization of component+residual (partial
residual) plots that are less prone to leakage of nonlinearity
among the predictors.
The function intended for direct use is `ceresPlots`

.
The model cannot contain interactions, but can contain factors.
Factors may be present in the model, but Ceres plots cannot be drawn
for them.

##### Value

`NULL`

. These functions are used for their side effect: producing plots.

##### References

Cook, R. D. and Weisberg, S. (1999)
*Applied Regression, Including Computing and Graphics.* Wiley.
Fox, J. (2008)
*Applied Regression Analysis and Generalized Linear Models*,
Second Edition. Sage.
Fox, J. and Weisberg, S. (2011)
*An R Companion to Applied Regression*, Second Edition, Sage.
Weisberg, S. (2005) *Applied Linear Regression*, Third Edition. Wiley.

##### See Also

##### Examples

`ceresPlots(lm(prestige~income+education+type, data=Prestige), terms= ~ . - type)`

*Documentation reproduced from package car, version 2.0-13, License: GPL (>= 2)*