| subsets {car} | R Documentation |
The regsubsets function in the leaps package finds
optimal subsets of predictors. This function plots a measure of fit
(see the statistic argument below) against subset size).
subsets(object, ...)
## S3 method for class 'regsubsets':
subsets(object,
names=abbreviate(object$xnames, minlength = abbrev),
abbrev=1, min.size=1, max.size=length(names), legend,
statistic=c("bic", "cp", "adjr2", "rsq", "rss"),
las=par('las'), cex.subsets=1, ...)
object |
a regsubsets object produced by the regsubsets function
in the leaps package. |
names |
a vector of (short) names for the predictors, excluding the
regression intercept, if one is present; if missing, these are
derived from the predictor names in object. |
abbrev |
minimum number of characters to use in abbreviating predictor names. |
min.size |
minimum size subset to plot; default is 1. |
max.size |
maximum size subset to plot; default is number of predictors. |
legend |
TRUE to plot a legend of predictor names; defaults to TRUE if abbreviations are computed for predictor names. The legend is placed on the plot interactively with the mouse. |
statistic |
statistic to plot for each predictor subset; one of:
"bic", Bayes Information Criterion;
"cp", Mallows's Cp;
"adjr2", R^2 adjusted for degrees of freedom;
"rsq", unadjusted R^2;
"rss", residual sum of squares. |
las |
if 0, ticks labels are drawn parallel to the
axis; set to 1 for horizontal labels (see par). |
cex.subsets |
can be used to change the relative size of the characters used to
plot the regression subsets; default is 1. |
... |
arguments to be passed down to
subsets.regsubsets and plot. |
NULL. This function is used for its side effect –
to create a plot.
John Fox
## Not run:
library(leaps)
subsets(regsubsets(undercount ~ ., data=Ericksen))
## End(Not run)