model {
  for (i in 1:n) {
    y[i] ~ dt(mu[i], #SIGMA, nu)
    mu[i] <- a0 + #FACTORS
  }
    
  #SIGMAPREC  
  
  # Baseline
  a0 ~ dnorm(y.mean, 1 / (y.sd * 5) ^ 2)
  
  #EFFECTS
  
  #MEANS
  
  sigma.r <- 1 + sigma.mode * sigma.l
  sigma.l <- ( sigma.mode + sqrt(sigma.mode ^ 2 + 4 * sigma.sd ^ 2) ) / (2 * sigma.sd ^ 2)
  sigma.mode ~ dgamma(x.gamma.prior[1], x.gamma.prior[2])
  sigma.sd ~ dgamma(x.gamma.prior[1], x.gamma.prior[2])
  nu <- nu.prec + 1
  nu.prec  ~ dexp(1 / 29)
}