\name{parseDist}
\alias{parseDist}
\alias{xmlDistribution}
\title{Translates between distribution object and <Distribution> XML}
\usage{ 
parseDist(xNode)
xmlDistribution(dist)
}
\arguments{
  \item{xNode}{\code{XMLNode} corresponding to a
    \code{<Distribution>} element.}
  \item{dist}{A \code{distribution} object.}
}
\description{
  The function \code{parseDist} decodes an \code{<Distribution>} element
  from a StatShop Graphical Model (GM) file and produces a
  \code{distribution} object.  The function \code{xmlDistribution} does
  the inverse.
}
\references{
  \url{http://research.ets.org/~ralmond/StatShop/dataFormats.html}
}
\author{Russell Almond}
\seealso{
  \code{\link[XML]{XMLNode}}, \code{\link{distribution}},
  \code{\link{getEMParametersForAMD}},\code{\link{getLMParametersForAMD}}
}
\examples{

  ## Pardon us while we build some distributions.
  ## Build the Parameter Set
  ## Need to get names correct for everything to work.
  pnames <- c("Task Difficulty", "Relative Importance(Reading)",
              "Level Difficulty Increment(Outcome_R,Good)")
  pvalue <- c(1,0,0.5)
  names(pvalue) <- pnames

  pcov <- matrix(0,nrow=length(pnames),ncol=length(pnames),
             dimnames=list(pnames,pnames))
  diag(pcov) <- c(0.3164,0.0207, 0.01)

  ps1 <- parameterVector(pvalue,"Outcome_R",pcov)  

  table1 <- matrix(c(0.79894674, 0.06863273, 0.1324205,
                    0.22270014, 0.09812116, 0.6791787,
                    0.02023846, 0.01269671, 0.9670648),nrow=3,byrow=3)
  ## These come from running calcDSTable with the above parameters.
  colnames(table1) <- c("Good","Okay","Poor")
  dtable1 <- data.frame(Reading=c("Advanced","Basic","Novice"),table1)

  ## DiBello--Samejima style
  dist1 <- distribution(c("Reading"),"Outcome_R",
                        "Compensatory Distribution", table=dtable1,
                        parameterSet = ps1)

  table2 <- matrix(c(0.7, 0.2, 0.1,
                     0.3, 0.4, 0.3,
                     0.1, 0.2, 0.7), nrow=3,byrow=3)
  ## These come from running calcDSTable with the above parameters.
  colnames(table2) <- c("Good","Okay","Poor")
  dtable2 <- data.frame(Reading=c("Advanced","Basic","Novice"),table2)
  ptable2 <- data.frame(Reading=c("Advanced","Basic","Novice"),table2,Scale=1,Sum=10)

  ## HyperDirichlet style
  dist2 <- distribution(c("Reading"),"Outcome_R",
                        "HyperDirichlet Distribution", table=dtable2,
                        parameterTable = ptable2)

  ## On to the real examples
  dist1node <- xmlDistribution(dist1)
  dist1rt <- parseDist(dist1node)

  dist2node <- xmlDistribution(dist2)
  dist2rt <- parseDist(dist2node)

  \dontshow{   
   ## For some reason identical fails, so need to do this the hardway
   stopifnot(
     identical(dist1$cond,dist1rt$cond),
     identical(dist1$cons,dist1rt$cons),
     identical(dist1$type,dist1rt$type),
     identical(dist1$table,dist1rt$table),
     identical(dist1$parameterSet,dist1rt$parameterSet),
     identical(dist1$parameterTable,dist1rt$parameterTable),

     identical(dist2$cond,dist2rt$cond),
     identical(dist2$cons,dist2rt$cons),
     identical(dist2$type,dist2rt$type),
     identical(dist2$table,dist2rt$table),
     identical(dist2$parameterSet,dist2rt$parameterSet),
     identical(dist2$parameterTable,dist2rt$parameterTable)
    )
}

}
\keyword{interface}