\name{parameterVector}
\alias{parameterVector}
\alias{show.parameterVector}
\title{
Creates a new parameter vector object.
}
\usage{
parameterVector(params, identifier=character(0), covariance=NULL)
show.parameterVector(object)
}

\arguments{
  \item{params}{A vector giving the values for the parameters.}
  \item{identifier}{A string giving the identifier for the model, this
    is usually of the form \code{\emph{model}.\emph{variable}}.}
  \item{covariance}{Either NULL or a covariance matrix.}
  \item{object}{A \code{parameterVector} we want to show.}
}
\value{
  An object of class \code{parameterVector}.  This represents the prior
  distribution for the parameters of a DiBello--Samejima type model.
  The \code{values} field gives the mean values for the parameter.  The
  \code{covariance} field (if non-\code{NULL} gives the covariance
  matrix.   The \code{identifier} field gives a string identifying the
  parameter.  
}
\description{
  Creates an object of \code{parameterVector}.  These are used to store
  the results of parsing the GM files associated with Assessment Model
  Description files.
}
\references{
  http://research.ets.org/~ralmond/StatShop/dataFormats.html
}
\seealso{
  \code{\link{distribution}}, \code{\link{parseParameterSet}}
}
\examples{

  ## Need to get names correct for everything to work.
  pnames <- c("Task Difficulty", "Relative Importance(Reading)",
              "Level Difficulty Increment(Outcome_R,Very Good)",
              "Level Difficulty Increment(Outcome_R,Good)")
  pvalue <- c(0,0.405,0.4837,0.4837)
  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, 0.01)

  ps1 <- parameterVector(pvalue,"SkillRead1.Outcome_R",pcov)  

}
\keyword{interface}