\name{actorAdjTable}
\alias{actorAdjTable}
\title{Compute actor size adjustment on a two way table}
\description{
  When two objects are related through a bipartite graph it is
  sometimes appropriate to carry out special adjustments. One of the
  adjustments is called actor size adjustment. In this case the counts
  are adjusted according to how often the objects are referenced.
}
\usage{
actorAdjTable(twT, eps = 1e-08)
}

\arguments{
  \item{twT}{ A two way table as produced by \code{\link{twowayTable}}. }
  \item{eps}{A small quantity used to assess approximate equality.}
}
\details{
 When testing for associations between entities, the social networks
  literature has developed a number of tools to help measure such
  associations.  We can think of genes (actors) as being joined by citation
  in papers (events) and having two genes cited in the same paper (equivalent
  to two actors attending the same event) suggests that they are related
  to each other.  However, some genes are cited in many papers and so
  we might want to discount the level of importance, as compared to genes
  that are cited less often. And additionally, some papers cite very
  many genes, and hence typically say less about them than a paper that
  cites rather fewer genes.
}
\value{
  An adjusted two way table, with elements named \code{u11},
  \code{u12}, \code{u21} and \code{u22}.
}
\references{Testing Gene Associations Using Co-citation, by B. Ding and
R. Gentleman. Bioconductor Technical Report, 2004}
\author{R. Gentleman}

\seealso{\code{\link{paperLen}}, \code{\link{twowayTable}} }

\examples{
  tw1 = twowayTable("10", "100", FALSE)
  actorAdjTable(tw1)

}
\keyword{manip}