for (i in 1:n_classes) {
    p[i] ~ beta(3,1);
    mus[i] ~ uniform(0, 1);
    etas[i] ~ pareto(1, 1.5);
}

for (c in 1:n_groups) {
    real ll_normal = 0;
    for (i in 1:n_classes) {
        ll_normal += beta_proportion_lpdf(lambda[c,i,:] | mus[i,:], etas[i,:])
    }
    // tolerance to outliers
    target += log_mix(0.025, 0, ll_normal);
}