Group generic methods can be defined for four pre-specified groups of
functions, `Math`

, `Ops`

, `Summary`

and `Complex`

.
(There are no objects of these names in base R, but there are in the
methods package.)

A method defined for an individual member of the group takes precedence over a method defined for the group as a whole.

```
## S3 methods for group generics have prototypes:
````Math(x, \dots)`

`Ops(e1, e2)`

`Complex(z)`

`Summary(\dots, na.rm = FALSE)`

x, z, e1, e2

objects.

…

further arguments passed to methods.

na.rm

logical: should missing values be removed?

These functions are all primitive and internal generic.

The details of method dispatch and variables such as `.Generic`

are discussed in the help for `UseMethod`

. There are a
few small differences:

For the operators of group

`Ops`

, the object`.Method`

is a length-two character vector with elements the methods selected for the left and right arguments respectively. (If no method was selected, the corresponding element is`""`

.)Object

`.Group`

records the group used for dispatch (if a specific method is used this is`""`

).

There are four *groups* for which S3 methods can be written,
namely the `"Math"`

, `"Ops"`

, `"Summary"`

and
`"Complex"`

groups. These are not R objects in base R, but
methods can be supplied for them and base R contains
`factor`

, `data.frame`

and
`difftime`

methods for the first three groups. (There is
also a `ordered`

method for `Ops`

,
`POSIXt`

and `Date`

methods for `Math`

and `Ops`

, `package_version`

methods for `Ops`

and `Summary`

, as well as a `ts`

method for
`Ops`

in package stats.)

Group

`"Math"`

:`abs`

,`sign`

,`sqrt`

,`floor`

,`ceiling`

,`trunc`

,`round`

,`signif`

`exp`

,`log`

,`expm1`

,`log1p`

,`cos`

,`sin`

,`tan`

,`cospi`

,`sinpi`

,`tanpi`

,`acos`

,`asin`

,`atan`

`cosh`

,`sinh`

,`tanh`

,`acosh`

,`asinh`

,`atanh`

`lgamma`

,`gamma`

,`digamma`

,`trigamma`

`cumsum`

,`cumprod`

,`cummax`

,`cummin`

Members of this group dispatch on

`x`

. Most members accept only one argument, but members`log`

,`round`

and`signif`

accept one or two arguments, and`trunc`

accepts one or more.Group

`"Ops"`

:`"+"`

,`"-"`

,`"*"`

,`"/"`

,`"^"`

,`"%%"`

,`"%/%"`

`"&"`

,`"|"`

,`"!"`

`"=="`

,`"!="`

,`"<"`

,`"<="`

,`">="`

,`">"`

This group contains both binary and unary operators (

`+`

,`-`

and`!`

): when a unary operator is encountered the`Ops`

method is called with one argument and`e2`

is missing.The classes of both arguments are considered in dispatching any member of this group. For each argument its vector of classes is examined to see if there is a matching specific (preferred) or

`Ops`

method. If a method is found for just one argument or the same method is found for both, it is used. If different methods are found, there is a warning about ‘incompatible methods’: in that case or if no method is found for either argument the internal method is used.If the members of this group are called as functions, any argument names are removed to ensure that positional matching is always used.

Group

`"Summary"`

:`all`

,`any`

`sum`

,`prod`

`min`

,`max`

`range`

Members of this group dispatch on the first argument supplied.

Group

`"Complex"`

:`Arg`

,`Conj`

,`Im`

,`Mod`

,`Re`

Members of this group dispatch on

`z`

.

Note that a method will be used for one of these groups or one of its
members *only* if it corresponds to a `"class"`

attribute,
as the internal code dispatches on `oldClass`

and not on
`class`

. This is for efficiency: having to dispatch on,
say, `Ops.integer`

would be too slow.

The number of arguments supplied for primitive members of the
`"Math"`

group generic methods is not checked prior to dispatch.

There is no lazy evaluation of arguments for group-generic functions.

Appendix A, *Classes and Methods* of
Chambers, J. M. and Hastie, T. J. eds (1992)
*Statistical Models in S.*
Wadsworth & Brooks/Cole.

`methods`

for methods of non-internal generic functions.

S4groupGeneric for group generics for S4 methods.

```
require(utils)
d.fr <- data.frame(x = 1:9, y = stats::rnorm(9))
class(1 + d.fr) == "data.frame" ##-- add to d.f. ...
methods("Math")
methods("Ops")
methods("Summary")
methods("Complex") # none in base R
```

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