`summary`

is a generic function used to produce result summaries
of the results of various model fitting functions. The function
invokes particular `methods`

which depend on the
`class`

of the first argument.

`summary(object, …)`# S3 method for default
summary(object, …, digits, quantile.type = 7)
# S3 method for data.frame
summary(object, maxsum = 7,
digits = max(3, getOption("digits")-3), …)

# S3 method for factor
summary(object, maxsum = 100, …)

# S3 method for matrix
summary(object, …)

# S3 method for summaryDefault
format(x, digits = max(3L, getOption("digits") - 3L), …)
# S3 method for summaryDefault
print(x, digits = max(3L, getOption("digits") - 3L), …)

object

an object for which a summary is desired.

x

a result of the *default* method of `summary()`

.

maxsum

integer, indicating how many levels should be shown for
`factor`

s.

digits

integer, used for number formatting with
`signif()`

(for `summary.default`

) or
`format()`

(for `summary.data.frame`

). In
`summary.default`

, if not specified (i.e.,
`missing(.)`

), `signif()`

will *not* be called
anymore (since R >= 3.4.0, where the default has been changed to
only round in the `print`

and `format`

methods).

quantile.type

integer code used in `quantile(*, type=quantile.type)`

for the default method.

…

additional arguments affecting the summary produced.

The form of the value returned by `summary`

depends on the
class of its argument. See the documentation of the particular
methods for details of what is produced by that method.

The default method returns an object of class
`c("summaryDefault", "table")`

which has specialized
`format`

and `print`

methods. The
`factor`

method returns an integer vector.

The matrix and data frame methods return a matrix of class
`"table"`

, obtained by applying `summary`

to each
column and collating the results.

For `factor`

s, the frequency of the first `maxsum - 1`

most frequent levels is shown, and the less frequent levels are
summarized in `"(Others)"`

(resulting in at most `maxsum`

frequencies).

The functions `summary.lm`

and `summary.glm`

are examples
of particular methods which summarize the results produced by
`lm`

and `glm`

.

Chambers, J. M. and Hastie, T. J. (1992)
*Statistical Models in S*.
Wadsworth & Brooks/Cole.

# NOT RUN { summary(attenu, digits = 4) #-> summary.data.frame(...), default precision summary(attenu $ station, maxsum = 20) #-> summary.factor(...) lst <- unclass(attenu$station) > 20 # logical with NAs ## summary.default() for logicals -- different from *.factor: summary(lst) summary(as.factor(lst)) # }

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