text: #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_RNG_HPP
  #define STAN_MATH_PRIM_SCAL_PROB_PARETO_RNG_HPP
  
  #include <stan/math/prim/meta.hpp>
  #include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
  #include <stan/math/prim/scal/err/check_positive_finite.hpp>
  #include <boost/random/exponential_distribution.hpp>
  #include <boost/random/variate_generator.hpp>
  
  namespace stan {
  namespace math {
  
  /** \ingroup prob_dists
   * Return a Pareto random variate for the given shape and scale
   * parameters using the specified random number generator.
   *
   * y_min and alpha can each be a scalar or a one-dimensional container. Any
   * non-scalar inputs must be the same size.
   *
   * @tparam T_scale Type of scale parameter
   * @tparam T_shape Type of shape parameter
   * @tparam RNG type of random number generator
   * @param y_min (Sequence of) positive scale parameter(s)
   * @param alpha (Sequence of) positive shape parameter(s)
   * @param rng random number generator
   * @return (Sequence of) Pareto random variate(s)
   * @throw std::domain_error if y_min or alpha are nonpositive
   * @throw std::invalid_argument if non-scalar arguments are of different
   * sizes
   */
  template <typename T_shape, typename T_scale, class RNG>
  inline typename VectorBuilder<true, double, T_shape, T_scale>::type pareto_rng(
      const T_scale& y_min, const T_shape& alpha, RNG& rng) {
    using boost::exponential_distribution;
    using boost::variate_generator;
  
    static const char* function = "pareto_rng";
  
    check_positive_finite(function, "Scale parameter", y_min);
    check_positive_finite(function, "Shape parameter", alpha);
    check_consistent_sizes(function, "Scale Parameter", y_min, "Shape parameter",
                           alpha);
  
    scalar_seq_view<T_scale> y_min_vec(y_min);
    scalar_seq_view<T_shape> alpha_vec(alpha);
    size_t N = max_size(y_min, alpha);
    VectorBuilder<true, double, T_scale, T_shape> output(N);
  
    for (size_t n = 0; n < N; ++n) {
      variate_generator<RNG&, exponential_distribution<> > exp_rng(
          rng, exponential_distribution<>(alpha_vec[n]));
      output[n] = y_min_vec[n] * std::exp(exp_rng());
    }
  
    return output.data();
  }
  
  }  // namespace math
  }  // namespace stan
  #endif
  