\HeaderA{diana.object}{Divisive Analysis (DIANA) Object}{diana.object}
\keyword{cluster}{diana.object}
\begin{Description}\relax
The objects of class \code{"diana"}
represent a divisive hierarchical clustering of a dataset.
\end{Description}
\begin{Value}
A legitimate \code{diana} object is a list with the following components:
\begin{ldescription}
\item[\code{order}] a vector giving a permutation of the original observations to allow for
plotting, in the sense that the branches of a clustering tree will
not cross.

\item[\code{order.lab}] a vector similar to \code{order}, but containing observation labels
instead of observation numbers.  This component is only available if
the original observations were labelled.

\item[\code{height}] a vector with the diameters of the clusters prior to splitting.

\item[\code{dc}] the divisive coefficient, measuring the clustering structure of the
dataset.  For each observation i, denote by \eqn{d(i)}{} the diameter of the
last cluster to which it belongs (before being split off as a single
observation), divided by the diameter of the whole dataset.  The
\code{dc} is the average of all \eqn{1 - d(i)}{}.  It can also be seen
as the average width (or the percentage filled) of the banner plot.
Because \code{dc} grows with the number of observations, this
measure should not be used to compare datasets of very different
sizes.

\item[\code{merge}] an (n-1) by 2 matrix, where n is the number of
observations. Row i of \code{merge} describes the split at step n-i of
the clustering. If a number \eqn{j}{} in row r is negative, then the single
observation \eqn{|j|}{} is split off at stage n-r. If j is positive, then the
cluster that will be splitted at stage n-j (described by row j), is
split off at stage n-r.

\item[\code{diss}] an object of class \code{"dissimilarity"}, representing the total
dissimilarity matrix of the dataset.

\item[\code{data}] a matrix containing the original or standardized measurements, depending
on the \code{stand} option of the function \code{agnes}.  If a
dissimilarity matrix was given as input structure, then this component
is not available.

\end{ldescription}
\end{Value}
\begin{Section}{GENERATION}
This class of objects is returned from \code{\LinkA{diana}{diana}}.
\end{Section}
\begin{Section}{METHODS}
The \code{"diana"} class has methods for the following generic functions:
\code{print}, \code{summary}, \code{plot}.
\end{Section}
\begin{Section}{INHERITANCE}
The class \code{"diana"} inherits from \code{"twins"}.
Therefore, the generic function \code{pltree} can be used on a
\code{diana} object, and an \code{\LinkA{as.hclust}{as.hclust}} method is
available.
\end{Section}
\begin{SeeAlso}\relax
\code{\LinkA{agnes}{agnes}}, \code{\LinkA{diana}{diana}}, \code{\LinkA{plot.diana}{plot.diana}},
\code{\LinkA{twins.object}{twins.object}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## really see example(diana) !   Additionally:
data(votes.repub)
dv0 <- diana(votes.repub, stand = TRUE)
## Cut into 2 groups:
dv2 <- cutree(as.hclust(dv0), k = 2)
table(dv2)
rownames(votes.repub)[dv2 == 1]
\end{ExampleCode}
\end{Examples}

