`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 = max(3, getOption("digits")-3))
# 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, …)

object

an object for which a summary is desired.

maxsum

integer, indicating how many levels should be shown for

`factor`

s.digits

…

additional arguments affecting the summary produced.

`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 a specialized
`print`

method. 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.`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`

.`anova`

,
`summary.glm`

,
`summary.lm`

.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))