crPlots {car}  R Documentation 
These functions construct component+residual plots, also called partialresidual plots, for linear and generalized linear models.
crPlots(model, ...) ## Default S3 method: crPlots(model, terms = ~., layout = NULL, ask, main, ...) crp(...) crPlot(model, ...) ## S3 method for class 'lm' crPlot(model, variable, id=FALSE, order=1, line=TRUE, smooth=TRUE, col=carPalette()[1], col.lines=carPalette()[1], xlab, ylab, pch=1, lwd=2, grid=TRUE, ...)
model 
model object produced by 
terms 
A onesided formula that specifies a subset of the regressors.
One componentplusresidual plot is drawn for each regressor. The default

layout 
If set to a value like 
ask 
If 
main 
The title of the plot; if missing, one will be supplied. 
... 

variable 
A quoted string giving the name of a variable for the horizontal axis. 
id 
controls point identification; if 
order 
order of polynomial regression performed for predictor to be plotted; default 
line 

smooth 
specifies the smoother to be used along with its arguments; if 
col 
color for points; the default is the first entry
in the current car palette (see 
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, 
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 
lwd 
line width; default is 
grid 
If TRUE, the default, a lightgray background grid is put on the graph. 
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.
NULL
. These functions are used for their side effect of producing
plots.
John Fox jfox@mcmaster.ca
Cook, R. D. and Weisberg, S. (1999) Applied Regression, Including Computing and Graphics. Wiley.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
crPlots(m<lm(prestige ~ income + education, data=Prestige)) crPlots(m, terms=~ .  education) # get only one plot crPlots(lm(prestige ~ log2(income) + education + poly(women,2), data=Prestige)) crPlots(glm(partic != "not.work" ~ hincome + children, data=Womenlf, family=binomial), smooth=list(span=0.75))