\HeaderA{lambda.reg.bayes}{Calculate shares using data from Bayesian regression model}{lambda.reg.bayes}
\keyword{models}{lambda.reg.bayes}
\begin{Description}\relax
Calculates the population share of row members in selected columns
\end{Description}
\begin{Usage}
\begin{verbatim}
lambda.reg.bayes(object, columns, ret.mcmc = TRUE) 
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{object}] An R object of class \code{eiRegBayes}, the output from \code{\LinkA{ei.reg.bayes}{ei.reg.bayes}}
\item[\code{columns}] a character vector indicating which column marginals to be included in calculating the shares
\item[\code{ret.mcmc}] If TRUE, posterior shares are returned as an \code{mcmc}
object.
\end{ldescription}
\end{Arguments}
\begin{Value}
If \code{ret.mcmc = TRUE}, draws are returned as an \code{mcmc} object
with dimensions sample \eqn{\times C}{}.  If \code{ret.mcmc =
    FALSE}, draws are returned as an array with dimensions \eqn{R
\times C \times }{} samples array.
\end{Value}
\begin{Author}\relax
Ryan T. Moore \textless{}\email{rtm@wustl.edu}\textgreater{}
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{ei.reg.bayes}{ei.reg.bayes}}
\end{SeeAlso}

