subsets | R Documentation |
The regsubsets
function in the leaps package finds
optimal subsets of predictors based on some criterion statistic. This function plots a measure of fit 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="interactive",
statistic=c("bic", "cp", "adjr2", "rsq", "rss"),
las=par('las'), cex.subsets=1, ...)
object |
a |
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 |
abbrev |
minimum number of characters to use in abbreviating predictor names. |
min.size |
minimum size subset to plot; default is |
max.size |
maximum size subset to plot; default is number of predictors. |
legend |
If not |
statistic |
statistic to plot for each predictor subset; one of:
|
las |
if |
cex.subsets |
can be used to change the relative size of the characters used to
plot the regression subsets; default is |
... |
arguments to be passed down to
|
NULL
if the legend
is TRUE
; otherwise a data frame with the legend.
John Fox
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.
regsubsets
if (require(leaps)){
subsets(regsubsets(undercount ~ ., data=Ericksen),
legend=c(3.5, -37))
}
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