\name{mvr}
\alias{mvr}
\title{Mean variance and R value.}
\description{
  This takes a \code{mcmc.list} object corresponding to a
  DiBello--Samejima model and calculates the mean and variance for each
  of the parameters plus a Gelman-Rubin R value for the parameter set.

}
\usage{
mvr(obj, pnames)
}
\arguments{
  \item{obj}{An \code{mcmc.list} object corresponding to a parameter set
  or else \code{NULL}.}
  \item{pnames}{A vector of parameter names.}
}
\details{
  The length of the returned vector depends on the length of the
  \code{pnames} argument.  The parameter set is trimmed or padded with
  \code{NA}s to match the length corresponding to the desired number of
  parameters.

  This assumes that the parameter are in the same order for every
  parameter set.

  If the first argument is \code{NULL} then returns a vector of
  \code{NA}s of the appropriate length.

}
\value{
  A vector of twice the length of \code{pnames} plus one.  These consist
  of the mean and variance entries followed by the Gelman-Rubin
  multivariate potential scale reduction factor.
}
\author{Russell Almond}
\seealso{\code{\link{buildRMatrix}},\code{\link{dsBuildRMatrix}},
  \code{\link{meanVar}},\code{\link[coda]{gelman.diag}}  }
\examples{\dontrun{
## Assumes all parameter sets have a single discrimination parameter.
meanVarTable <- dsBuildRMatrix(dc,mvr,
                                  c("Difficulty","logDisc","DiffInc"),
                                  maxparams=15)
}
}

\keyword{ts}