\HeaderA{setOldClass}{Specify Names for Old-Style Classes}{setOldClass}
\aliasA{.OldClassesList}{setOldClass}{.OldClassesList}
\aliasA{.setOldIs}{setOldClass}{.setOldIs}
\aliasA{anova-class}{setOldClass}{anova.Rdash.class}
\aliasA{anova.glm-class}{setOldClass}{anova.glm.Rdash.class}
\aliasA{anova.glm.null-class}{setOldClass}{anova.glm.null.Rdash.class}
\aliasA{aov-class}{setOldClass}{aov.Rdash.class}
\aliasA{data.frame-class}{setOldClass}{data.frame.Rdash.class}
\aliasA{density-class}{setOldClass}{density.Rdash.class}
\aliasA{dump.frames-class}{setOldClass}{dump.frames.Rdash.class}
\aliasA{factor-class}{setOldClass}{factor.Rdash.class}
\aliasA{formula-class}{setOldClass}{formula.Rdash.class}
\aliasA{glm-class}{setOldClass}{glm.Rdash.class}
\aliasA{glm.null-class}{setOldClass}{glm.null.Rdash.class}
\aliasA{hsearch-class}{setOldClass}{hsearch.Rdash.class}
\aliasA{initialize,data.frame-method}{setOldClass}{initialize,data.frame.Rdash.method}
\aliasA{initialize,factor-method}{setOldClass}{initialize,factor.Rdash.method}
\aliasA{initialize,ordered-method}{setOldClass}{initialize,ordered.Rdash.method}
\aliasA{initialize,summary.table-method}{setOldClass}{initialize,summary.table.Rdash.method}
\aliasA{initialize,table-method}{setOldClass}{initialize,table.Rdash.method}
\aliasA{integrate-class}{setOldClass}{integrate.Rdash.class}
\aliasA{libraryIQR-class}{setOldClass}{libraryIQR.Rdash.class}
\aliasA{lm-class}{setOldClass}{lm.Rdash.class}
\aliasA{logLik-class}{setOldClass}{logLik.Rdash.class}
\aliasA{maov-class}{setOldClass}{maov.Rdash.class}
\aliasA{mlm-class}{setOldClass}{mlm.Rdash.class}
\aliasA{mtable-class}{setOldClass}{mtable.Rdash.class}
\aliasA{mts-class}{setOldClass}{mts.Rdash.class}
\aliasA{oldClass-class}{setOldClass}{oldClass.Rdash.class}
\aliasA{ordered-class}{setOldClass}{ordered.Rdash.class}
\aliasA{packageInfo-class}{setOldClass}{packageInfo.Rdash.class}
\aliasA{packageIQR-class}{setOldClass}{packageIQR.Rdash.class}
\aliasA{POSIXct-class}{setOldClass}{POSIXct.Rdash.class}
\aliasA{POSIXlt-class}{setOldClass}{POSIXlt.Rdash.class}
\aliasA{POSIXt-class}{setOldClass}{POSIXt.Rdash.class}
\aliasA{recordedplot-class}{setOldClass}{recordedplot.Rdash.class}
\aliasA{rle-class}{setOldClass}{rle.Rdash.class}
\aliasA{socket-class}{setOldClass}{socket.Rdash.class}
\aliasA{summary.table-class}{setOldClass}{summary.table.Rdash.class}
\aliasA{table-class}{setOldClass}{table.Rdash.class}
\keyword{programming}{setOldClass}
\keyword{methods}{setOldClass}
\begin{Description}\relax
Register an old-style (a.k.a. \sQuote{S3}) class as a formally defined
class. The \code{Classes} argument is the character vector used as the
\code{class} attribute; in particular, if there is more than one
string,  old-style class inheritance is mimicked.  Registering via
\code{setOldClass} allows S3 classes to appear  in method
signatures, and as a slot in an S4 class if a prototype is included.
\end{Description}
\begin{Usage}
\begin{verbatim}
setOldClass(Classes, prototype, where, test = FALSE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{Classes}] A character vector, giving the names for old-style
classes, as they would appear on the right side of an assignment of
the \code{class} attribute.

\item[\code{prototype}] An optional object to use as the prototype.  This should be provided
as the default S3 object for the class, if you plan to use the class as
a slot in an S4 class.  See the details section.

\item[\code{where}] Where to store the class definitions, the global or top-level
environment by default.  (When either function is called in the
source for a package, the class definitions will be included in the
package's environment by default.)

\item[\code{test}] flag, if \code{TRUE}, inheritance must be tested
explicitly for each object, needed if the S3 class can have a
different set of class strings, with the same first string.
See the details below.

\end{ldescription}
\end{Arguments}
\begin{Details}\relax
Each of the names will be defined as an S4 class, extending the
remaining classes in \code{Classes}, and the class \code{oldClass},
which is the \sQuote{root} of all old-style classes. S3 classes have
no formal definition, and therefore no formally defined slots. If a
\code{prototype} argument is supplied in the call to
\code{setOldClass()}, objects from the class can be generated. If the
S3 class is to be a slot in an S4 class, providing a prototype is
recommended. Otherwise, the class will be created as a virtual S4
class; method dispatch will still work and inheritance will follow the
S3 class hierarchy, but actions that require a prototype object from
the class will not. For example, using the class as a slot in an S4
class definition will set the corresponding slot to \code{NULL} in the
prototype for the S4 class.

Providing a prototype allows the function \code{new()} to be called
for this class, but optional arguments in this call are not
meaningful, since the class has no formal slots. Extending an S3 class
with an S4 class is formally legal, but discouraged. Since the S4
subclass will have a single character string in its \code{class()}, S3
inheritance will not work. Also, there is no safe way for a general
object from the S3 class to be inserted when an object is generated
from the subclass.

See \LinkA{Methods}{Methods} for the details of method dispatch and
inheritance. See the section \bold{Register or Convert?} for
comments on the alternative of defining \sQuote{real} S4 classes
rather than using \code{setOldClass}.

Some S3 classes cannot be represented as an ordinary combination of S4
classes and superclasses, because objects from the S3 class can have a
variable set of strings in the class. It is still possible to register
such classes as S4 classes, but now the inheritance has to be verified
for each object, and you must call \code{setOldClass} with argument
\code{test=TRUE} once for each superclass.

For example, ordered factors \emph{always} have the S3
class \code{c("ordered", "factor")}.  This is proper behavior, and
maps simply into two S4 classes, with \code{"ordered"} extending
\code{"factor"}.

But objects whose class attribute has \code{"POSIXt"} as the first
string may have either (or neither) of \code{"POSIXct"} or
\code{"POSIXlt"} as the second string.  This behavior can be mapped
into S4 classes but now to evaluate \code{is(x, "POSIXlt")}, for
example, requires checking the S3 class attribute on each object.
Supplying the \code{test=TRUE} argument to \code{setOldClass} causes
an explicit test to be included in the class definitions.  It's
never wrong to have this test, but since it adds significant
overhead to methods defined for the inherited classes, you should
only supply this argument if it's known that object-specific tests
are needed.

The list \code{.OldClassesList} contains the old-style classes that
are defined by the methods package.  Each element of the list is an
old-style list, with multiple character strings if inheritance is
included.
Each element of the list was passed to \code{setOldClass} when
creating the \pkg{methods} package; therefore, these classes can be used
in \code{\LinkA{setMethod}{setMethod}} calls, with the inheritance as implied by
the list.
\end{Details}
\begin{Section}{Register or Convert?}
A call to \code{setOldClass} creates formal classes corresponding
to S3 classes, allows these to be used as slots in other classes or in
a signature in \code{\LinkA{setMethod}{setMethod}}, and mimics the S3 inheritance.

Supplying the \code{prototype} and optionally the \code{generator} arguments allows the S4 class created to be non-virtual, making it a candidate to be a slot in S4 class definitions and to be extended by  S4 classes.
The class still does not have formally defined slots.
Because R implements slots as attributes, an S3 class that uses attributes (\code{factor}, for example) can in principle be defined as an S4 class with slots.
However, a class such as \code{lm} that uses components of a list in a similar role cannot have formal slots.
The slots would  not be interpreted by S3 code written for \code{lm} objects.

\emph{If} your class does in fact have a consistent set of attributes, so that
every object from the class has the same structure, you may prefer to
take some extra time to write down a specific definition in a call to
\code{\LinkA{setClass}{setClass}} to convert the class to a fully functional
formal class.  On the other hand, if the actual contents of the class
vary from one object to another, such a definition will not generally be possible.  You should still register the class via
\code{setOldClass}, unless its class attribute is hopelessly unpredictable.

An S3 class has consistent structure if each object has the same set
of attributes, both the names and the classes of the attributes being
the same for every object in the class.  In practice, you can convert
classes that are slightly less well behaved.  If a few attributes
appear in some but not all objects, you can include these optional
attributes as slots that \emph{always} appear in the objects, if you
can supply a default value that is equivalent to the attribute being
missing.  Sometimes \code{NULL} can be that value: A slot (but not an
attribute) can have the value \code{NULL}.  If \code{version}, for
example, was an optional attribute, the old test
\code{is.null(attr(x,"version")} for a missing version attribute could
turn into \code{is.null(x@version)} for the formal class.

The requirement that slots have a fixed class can be satisfied
indirectly as well.  Slots \emph{can} be specified with class
\code{"ANY"}, allowing an arbitrary object.  However, this eliminates
an important benefit of formal class definitions; namely, automatic
validation of objects assigned to a slot.  If just a few different
classes are possible, consider using \code{\LinkA{setClassUnion}{setClassUnion}} to
define valid objects for a slot.
\end{Section}
\begin{SeeAlso}\relax
\code{\LinkA{setClass}{setClass}}, \code{\LinkA{setMethod}{setMethod}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}

require(stats)
setOldClass(c("mlm", "lm"))
setGeneric("dfResidual", function(model)standardGeneric("dfResidual"))
setMethod("dfResidual", "lm", function(model)model$df.residual)

## dfResidual will work on mlm objects as well as lm objects
myData <- data.frame(time = 1:10, y = (1:10)^.5)
myLm <- lm(cbind(y, y^3)  ~ time, myData)



rm(myData, myLm)
removeGeneric("dfResidual")
## Not run: setOldClass("data.frame", prototoype = data.frame())

## End(Not run)
\end{ExampleCode}
\end{Examples}

