leverage.plots {car} | R Documentation |
These functions display a generalization, due to Sall (1990), of added-variable plots to multiple-df terms in a linear model. When a term has just 1 df, the leverage plot is a rescaled version of the usual added-variable (partial-regression) plot.
leverage.plots(model, term.name, ask=missing(term.name), ...) leverage.plot(model, ...) ## S3 method for class 'lm': leverage.plot(model, term.name, labels=names(residuals(model)[!is.na(residuals(model))]), identify.points=TRUE, las=par('las'), col=palette()[2], pch=1, lwd=2, main="Leverage Plot", ...) ## S3 method for class 'glm': leverage.plot(model, ...)
model |
model object produced by lm |
term.name |
name of term in the model to be plotted; this argument is usually
omitted for leverage.plots . |
ask |
if TRUE , a menu is provided in the R Console for the
user to select the term(s) to plot. |
labels |
observation names. |
identify.points |
if TRUE , then identify points interactively. |
las |
if 0 , ticks labels are drawn parallel to the
axis; set to 1 for horizontal labels (see par ). |
col |
color for points and lines; the default is the second entry
in the current color palette (see palette
and par ). |
pch |
plotting character for points; default is 1
(a circle, see par ). |
lwd |
line width; default is 2 (see par ). |
main |
title for plot. |
... |
arguments passed down to method functions. |
The function intended for direct use is leverage.plots
. By default, this
function is used interactively through a text menu.
The model can contain factors and interactions. A leverage plot can be drawn for each term in the model, including the constant.
leverage.plot.glm
is a dummy function, which generates an error message.
NULL
. These functions are used for their side effect: producing
plots.
John Fox jfox@mcmaster.ca
Fox, J. (1997) Applied Regression, Linear Models, and Related Methods. Sage.
Sall, J. (1990) Leverage plots for general linear hypotheses. American Statistician 44, 308–315.
## Not run: leverage.plots(lm(prestige~(income+education)*type, data=Duncan)) ## End(Not run)