car (version 2.0-8)

crPlots: Component+Residual (Partial Residual) Plots

Description

These functions construct component+residual plots (also called partial-residual plots) for linear and generalized linear models.

Usage

crPlots(model, terms = ~., layout = NULL, ask, main, 
    ...)

crp(...)

crPlot(model, ...)

## S3 method for class 'lm':
crPlot(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],
  order=1, line=TRUE, smooth=TRUE,
	iter, span=.5, 
  col=palette()[1], col.lines=palette()[-1],
  xlab, ylab, pch=1, lwd=2, grid=TRUE, ...)

## S3 method for class 'glm':
crPlot(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 layo

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

The title of the plot; if missing, one will be supplied.

...

crPlots passes these arguments to crPlot. crPlot 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.

order

order of polynomial regression performed for predictor to be plotted; default 1.

line

TRUE to plot least-squares line.

smooth

TRUE to plot nonparametric-regression (lowess) line.

iter

number of robustness iterations for nonparametric-regression smooth; defaults to 3 for a linear model and to 0 for a non-Gaussian glm.

span

span for lowess smoother.

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

Value

• NULL. These functions are used for their side effect of producing plots.

Details

The function intended for direct use is crPlots, for which crp is an abbreviation. The model cannot contain interactions, but can contain factors. Parallel boxplots of the partial residuals are drawn for the levels of a factor.

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.

See Also

ceresPlots, avPlots

Examples

crPlots(m<-lm(prestige~income+education, data=Prestige)) 
# get only one plot
crPlots(m, terms=~ . - education)

crPlots(lm(prestige ~ log2(income) + education + poly(women,2), data=Prestige))

crPlots(glm(partic != "not.work" ~ hincome + children, 
  data=Womenlf, family=binomial))