leveragePlots(model, terms = ~., layout = NULL, ask,
main, ...)
leveragePlot(model, ...)
## S3 method for class 'lm':
leveragePlot(model, term.name,
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],
col=palette()[1], col.lines=palette()[2], lwd=2,
xlab, ylab, main="Leverage Plot", grid=TRUE, ...)
## S3 method for class 'glm':
leveragePlot(model, ...)
lm
~.
is to plot against all numeric predictors. For example, the
specification terms = ~ . - X3
would 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 laTRUE
, a menu is provided in the R Console for the
user to select the term(s) to plot.leveragePlots
.id.n=0
for labeling no points. See
showLabels
for details of these arguments.2
(see par
).NULL
. These functions are used for their side effect: producing
plots.leveragePlots
.
The model can contain factors and interactions. A leverage plot can be
drawn for each term in the model, including the constant.
leveragePlot.glm
is a dummy function, which generates an error message.avPlots
leveragePlots(lm(prestige~(income+education)*type, data=Duncan))
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