\name{buildRMatrix}
\alias{buildRMatrix}
\title{Builds a matrix summarizing parameters for a daCapo object}
\description{
  This applies \code{sumFun} to each link model parameter set in a \code{daCapo}
  object and returns a big data frame giving the result of the function
  for each object.  The summary function, \code{sumFun}, should return a
  vector of the same length for each object.
}
\usage{
buildRMatrix(dc, sumFun, ..., whichLinkModels=1:length(dc$linkModels))
}
\arguments{
  \item{dc}{A \code{daCapo} object giving the results from a StatShop run.}
  \item{sumFun}{A summary function for a parameter set.  This function
    should return a labeled vector of statistics for the parameter set.
    It could also return \code{NA} if the parameter set was \code{NA}
    (due to thining).}
  \item{\dots}{Additional arguments passed to \code{sumFun}.}
  \item{whichLinkModels}{Additional arguments passed to \code{sumFun}.}
}
\value{
  A \code{data.frame} giving the results for each parameter set.  The
  first three columns provide the name of the task, the name of the
  evidence model and the name of the observable respectively.
}
\note{
  The function \code{dsBuildRMatrix} does much the same work as
  \code{daCapo} followed by  \code{buildRMatrix} without producing the
  large \code{daCapo} object.  Using \code{daCapo} is more efficient if
  multiple analyses of the same data are required, however, it may not
  work due to memory limitiations on some systems (especially Windows).
}
\author{Russell Almond}
\seealso{\code{\link{daCapo}},\code{\link{meanVar}}, \code{\link{mvr}}}
\examples{\dontrun{
dc <- daCapo(maxparams=15)
meanVarTable <-
buildRMatrix(dc,meanVar,c("Difficulty","logDisc","DiffInc"))
}
}
\keyword{utilities}% at least one, from doc/KEYWORDS