crPlots  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, ...)
crPlot3d(model, var1, var2, ...)
## S3 method for class 'lm'
crPlot3d(model, var1, var2,
xlab = var1,
ylab = paste0("C+R(", eff$response, ")"), zlab = var2,
axis.scales = TRUE, axis.ticks = FALSE, revolutions = 0,
bg.col = c("white", "black"),
axis.col = if (bg.col == "white") c("darkmagenta", "black", "darkcyan")
else c("darkmagenta", "white", "darkcyan"),
surface.col = carPalette()[2:3], surface.alpha = 0.5,
point.col = "yellow", text.col = axis.col,
grid.col = if (bg.col == "white") "black" else "gray",
fogtype = c("exp2", "linear", "exp", "none"),
fill = TRUE, grid = TRUE, grid.lines = 26,
smoother = c("loess", "mgcv", "none"), df.mgcv = NULL, loess.args = NULL,
sphere.size = 1, radius = 1, threshold = 0.01, speed = 1, fov = 60,
ellipsoid = FALSE, level = 0.5, ellipsoid.alpha = 0.1,
id = FALSE,
mouseMode=c(none="none", left="polar", right="zoom", middle="fov",
wheel="pull"),
...)
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

var1, var2 
The quoted names of the two predictors in the model to use for a 3D C+R plot. 
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 
smoother, df.mgcv, loess.args 

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, zlab 
labels for the x and y axes, and for the z axis of a 3D plot. If not set appropriate labels are created by the function. for the 3D C+R plot, the predictors are on the x and z axes and the response on the y (vertical) axis. 
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. For a 3D C+R plot, see the 
grid.lines 
number of horizontal and vertical lines to be drawn on
regression surfaces for 2D C+R plots (26 by default); the square of 
axis.scales, axis.ticks, revolutions, bg.col,
axis.col, surface.col, surface.alpha,
point.col, text.col, grid.col, fogtype, fill,
sphere.size, radius, threshold, speed, fov,
ellipsoid, level, ellipsoid.alpha, mouseMode 
see 
The functions intended for direct use are crPlots
, for which crp
is an abbreviation, and, for 3D C+R plots, crPlot3d
.
For 2D plots, the model cannot contain interactions, but can contain factors.
Parallel boxplots of the partial residuals are drawn for the levels
of a factor. crPlot3d
can handle models with twoway interactions.
For 2D C+R plots, the fit is represented by a broken blue line and a smooth of the partial residuals by a solid magenta line. For 3D C+R plots, the fit is represented by a blue surface and a smooth of the partial residuals by a magenta surface.
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.
ceresPlots
, avPlots
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))
# 3D C+R plot, requires the rgl, effects, and mgcv packages
if (interactive() && require(rgl) && require(effects) && require(mgcv)){
crPlot3d(lm(prestige ~ income*education + women, data=Prestige),
"income", "education")
}
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