crPlots | R Documentation |
These functions construct component+residual plots, also called partial-residual 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 one-sided formula that specifies a subset of the regressors.
One component-plus-residual 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 light-gray 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 two-way 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.
These functions are used for their side effect of producing plots, but also invisibly return the coordinates of the plotted points.
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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