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 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, ...)

`NULL`

if the `legend`

is `TRUE`

; otherwise a data frame with the legend.

- 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
If not

`FALSE`

, in which case the legend is suppressed, the coordinates at which to place a legend of the abbreviated predictor names on the plot, in a form recognized by the`legend`

function. If`"interactive"`

, the legend is placed on the plot interactively with the mouse. By expanding the left or right plot margin, you can place the legend in the margin, if you wish (see`par`

).- statistic
statistic to plot for each predictor subset; one of:

`"bic"`

, Bayes Information Criterion;`"cp"`

, Mallows's \(C_{p}\);`"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`

.

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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