model {

  mu ~ dnorm( 0.0, 1.0E-6 )
  log.tau ~ dnorm( 0.0, 1.0E-6 )

  for ( i in 1:n ) {

    y[ i ] ~ dlnorm( mu, tau )

  }

  tau <- exp( log.tau )
  sigma.squared <- 1.0 / tau
  theta <- exp( mu + 
    sigma.squared / 2 )
  y.new ~ dlnorm( mu, tau )

}