// Arguments: Doubles, Doubles
#include <stan/math/prim.hpp>

using stan::math::var;
using std::numeric_limits;
using std::vector;

class AgradDistributionsChiSquare : public AgradDistributionTest {
 public:
  void valid_values(vector<vector<double> >& parameters,
                    vector<double>& log_prob) {
    vector<double> param(2);

    param[0] = 7.9;  // y
    param[1] = 3.0;  // nu
    parameters.push_back(param);
    log_prob.push_back(-3.835507153468185048695);  // expected log_prob

    param[0] = 1.9;  // y
    param[1] = 0.5;  // nu
    parameters.push_back(param);
    log_prob.push_back(-2.892699734467359284906);  // expected log_prob
  }

  void invalid_values(vector<size_t>& index, vector<double>& value) {
    // y

    // nu
    index.push_back(1U);
    value.push_back(0.0);

    index.push_back(1U);
    value.push_back(-1.0);

    index.push_back(1U);
    value.push_back(numeric_limits<double>::infinity());
  }

  template <typename T_y, typename T_dof, typename T2, typename T3, typename T4,
            typename T5>
  stan::return_type_t<T_y, T_dof, T2> log_prob(const T_y& y, const T_dof& nu,
                                               const T2&, const T3&, const T4&,
                                               const T5&) {
    return stan::math::chi_square_log(y, nu);
  }

  template <bool propto, typename T_y, typename T_dof, typename T2, typename T3,
            typename T4, typename T5>
  stan::return_type_t<T_y, T_dof> log_prob(const T_y& y, const T_dof& nu,
                                           const T2&, const T3&, const T4&,
                                           const T5&) {
    return stan::math::chi_square_log<propto>(y, nu);
  }

  template <typename T_y, typename T_dof, typename T2, typename T3, typename T4,
            typename T5>
  stan::return_type_t<T_y, T_dof> log_prob_function(const T_y& y,
                                                    const T_dof& nu, const T2&,
                                                    const T3&, const T4&,
                                                    const T5&) {
    using boost::math::lgamma;
    using stan::math::HALF_LOG_TWO;
    using stan::math::multiply_log;

    return -nu * HALF_LOG_TWO - lgamma(0.5 * nu)
           + multiply_log(0.5 * nu - 1.0, y) - 0.5 * y;
  }
};
