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\name{rtrun}
\alias{rtrun}
\concept{truncated normal}
\concept{simulation}
\title{Draw from Truncated Univariate Normal}
\description{
\code{rtrun} draws from a truncated univariate normal distribution.
}
\usage{rtrun(mu, sigma, a, b)}
\arguments{
\item{mu}{ mean }
\item{sigma}{ standard deviation }
\item{a}{ lower bound }
\item{b}{ upper bound }
}
\details{
Note that due to the vectorization of the \code{rnorm} and \code{qnorm} commands in R, all arguments can be vectors of equal length. This makes the inverse CDF method the most efficient to use in R.
}
\value{Draw (possibly a vector)}
\section{Warning}{
This routine is a utility routine that does \strong{not} check the input arguments for proper dimensions and type.
**Note also that \code{rtrun} is currently affected by the numerical accuracy of the inverse CDF function when trunctation points are far out in the tails of the distribution, where \dQuote{far out} means \eqn{|a - \mu| / \sigma > 6} and/or \eqn{|b - \mu| / \sigma > 6}. A fix will be implemented in a future version of \code{bayesm}.
}
\author{Peter Rossi, Anderson School, UCLA, \email{perossichi@gmail.com}.}
\references{For further discussion, see Chapter 2, \emph{Bayesian Statistics and Marketing} by Rossi, Allenby, and McCulloch.}
\examples{
set.seed(66)
rtrun(mu=c(rep(0,10)), sigma=c(rep(1,10)), a=c(rep(0,10)), b=c(rep(2,10)))
}
\keyword{distribution}
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