\name{drawEMParam}
\alias{drawEMParam}
\alias{lpriorEMParam}
\title{Draws a value of the parameter set for an EvidenceModel 
}
\description{

  Each \code{\link{EvidenceModel}} object should contain a prior
  distribtion for its parameter object.  The \code{drawEMParam} function
  draws a random set of values for the parameter object from that
  distribution.  The \code{lpriorEMParam} function calculates the log of
  the prior probability of a given parameter.
  
}
\usage{
drawEMParam(em, background = NA, QQ=Q(em))
lpriorEMParam(em, param=parameters(em), background = NA, QQ=Q(em))
}
\arguments{
  \item{em}{
    An object of class \code{\link{EvidenceModel}}.
  }
  \item{param}{
    A set of parameters whose prior distribution is to be evaluated.
  }
  \item{background}{
    An optional set of background (demographic) variables.  Some
    evidence model types ignore background variables.
  }
  \item{QQ}{A Q-matrix to use (only needed if different from the one
    stored with the evidence model).}
}
\value{
  The function \code{drawEMParam} parameter object of a class
  appropriate for use with the \code{em} argument.

  The function \code{lpriorEMParam} returns a scalar giving the log of
  the prior probability of the argument.
}
\references{
%% ~put references to the literature/web site here ~
}
\author{Russell Almond}

\seealso{
  \code{\link{EvidenceModel}}
}
\examples{
Q <- matrix(c(1,0,1,1),2,2)
em1 <- new("FixedQNormalEM", Q=Q,
           zMean=c(Mechanics=0,Fluency=0),  zStd=diag(c(1,1)),
           Rmean=matrix(c(.7,.3,.3,.7),2,2), Rdf=3,
           hMean=c(1,1,.5), hStd=rep(.25,3))


em1.p1 <- drawEMParam(em1)
lpriorEMParam(em1,em1.p1)


}
\keyword{ distribution }
\keyword{ random }