# ceresPlots

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##### 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
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.

crPlots, avPlots, showLabels

##### Aliases
• ceresPlots
• ceresPlot
• ceresPlot.lm
• ceresPlot.glm
##### Examples
ceresPlots(lm(prestige~income+education+type, data=Prestige), terms= ~ . - type)
Documentation reproduced from package car, version 2.0-11, License: GPL (>= 2)

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