{

  gamma.0 ~ dnorm( 0.0, 1.0E-4 )
  gamma.1 ~ dnorm( 0.0, 1.0E-4 )
  sigma.e ~ dunif( 0.0, 2.0 )

  for ( i in 1:n ) {

    e[ i ] ~ dnorm( 0.0, tau.e )
    log( lambda[ i ] ) <- gamma.0 + 
      gamma.1 * x[ i ] + e[ i ]
    y[ i ] ~ dpois( lambda[ i ] )

  }

  lambda.C <- exp( gamma.0 )
  lambda.E <- exp( gamma.0 + gamma.1 )
  mult.effect <- exp( gamma.1 )
  tau.e <- 1.0 / pow( sigma.e, 2 )

  big.mult.effect <- step( 1.0 - mult.effect )

}