#ifndef STAN__MATH__PRIM__SCAL__PROB__EXP_MOD_NORMAL_CCDF_LOG_HPP
#define STAN__MATH__PRIM__SCAL__PROB__EXP_MOD_NORMAL_CCDF_LOG_HPP

#include <boost/random/normal_distribution.hpp>
#include <boost/math/special_functions/fpclassify.hpp>
#include <boost/random/variate_generator.hpp>
#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
#include <stan/math/prim/scal/err/check_finite.hpp>
#include <stan/math/prim/scal/err/check_not_nan.hpp>
#include <stan/math/prim/scal/err/check_positive_finite.hpp>
#include <stan/math/prim/scal/fun/constants.hpp>

#include <stan/math/prim/scal/meta/constants.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>
#include <stan/math/prim/scal/fun/value_of.hpp>

namespace stan {

  namespace prob {

    template <typename T_y, typename T_loc, typename T_scale, 
              typename T_inv_scale>
    typename return_type<T_y,T_loc,T_scale,T_inv_scale>::type
    exp_mod_normal_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma, 
                            const T_inv_scale& lambda) {
      static const char* function("stan::prob::exp_mod_normal_ccdf_log");
      typedef typename stan::partials_return_type<T_y,T_loc,T_scale,
                                                  T_inv_scale>::type
        T_partials_return;

      using stan::math::check_positive_finite;
      using stan::math::check_finite;
      using stan::math::check_not_nan;
      using stan::math::check_consistent_sizes;
      using stan::math::value_of;

      T_partials_return ccdf_log(0.0);
      //check if any vectors are zero length
      if (!(stan::length(y) 
            && stan::length(mu) 
            && stan::length(sigma)
            && stan::length(lambda)))
        return ccdf_log;

      check_not_nan(function, "Random variable", y);
      check_finite(function, "Location parameter", mu);
      check_not_nan(function, "Scale parameter", sigma);
      check_positive_finite(function, "Scale parameter", sigma);
      check_positive_finite(function, "Inv_scale parameter", lambda);
      check_not_nan(function, "Inv_scale parameter", lambda);
      check_consistent_sizes(function,
                             "Random variable",y,
                             "Location parameter", mu,
                             "Scale parameter", sigma,
                             "Inv_scale paramter", lambda);
      

      agrad::OperandsAndPartials<T_y, T_loc, T_scale, T_inv_scale> 
        operands_and_partials(y, mu, sigma,lambda);

      using stan::math::SQRT_2;
      using std::log;

      VectorView<const T_y> y_vec(y);
      VectorView<const T_loc> mu_vec(mu);
      VectorView<const T_scale> sigma_vec(sigma);
      VectorView<const T_inv_scale> lambda_vec(lambda);
      size_t N = max_size(y, mu, sigma, lambda);
      const double sqrt_pi = std::sqrt(stan::math::pi());
      for (size_t n = 0; n < N; n++) {

        if(boost::math::isinf(y_vec[n])) {
          if (y_vec[n] > 0.0)
            return operands_and_partials.to_var(stan::math::negative_infinity(),
                                                y,mu,sigma,lambda);
          else
            return operands_and_partials.to_var(0.0,y,mu,sigma,lambda);
        }

        const T_partials_return y_dbl = value_of(y_vec[n]);
        const T_partials_return mu_dbl = value_of(mu_vec[n]);
        const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
        const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
        const T_partials_return u = lambda_dbl * (y_dbl - mu_dbl);
        const T_partials_return v = lambda_dbl * sigma_dbl ;
        const T_partials_return v_sq = v * v;
        const T_partials_return scaled_diff = (y_dbl - mu_dbl) 
          / (SQRT_2 * sigma_dbl);
        const T_partials_return scaled_diff_sq = scaled_diff * scaled_diff;
        const T_partials_return erf_calc1 = 0.5 * (1 + erf(u / (v * SQRT_2)));
        const T_partials_return erf_calc2 = 0.5 * (1 + erf(u / (v * SQRT_2) 
                                                           - v / SQRT_2));

        const T_partials_return deriv_1 = lambda_dbl * exp(0.5 * v_sq - u) 
          * erf_calc2;
        const T_partials_return deriv_2 = SQRT_2 / sqrt_pi * 0.5 
          * exp(0.5 * v_sq 
                - (-scaled_diff + (v / SQRT_2)) * (-scaled_diff  
                                                   + (v / SQRT_2)) - u) 
          / sigma_dbl;
        const T_partials_return deriv_3 = SQRT_2 / sqrt_pi * 0.5 
          * exp(-scaled_diff_sq) / sigma_dbl;

        const T_partials_return ccdf_ = 1.0 - erf_calc1 + exp(-u + v_sq * 0.5) 
          * (erf_calc2);

        ccdf_log += log(ccdf_);

        if (!is_constant_struct<T_y>::value)
          operands_and_partials.d_x1[n]
            -= (deriv_1 - deriv_2 + deriv_3) / ccdf_;
        if (!is_constant_struct<T_loc>::value)
          operands_and_partials.d_x2[n] 
            -= (-deriv_1 + deriv_2 - deriv_3) / ccdf_;
        if (!is_constant_struct<T_scale>::value)
          operands_and_partials.d_x3[n] 
            -= (-deriv_1 * v - deriv_3 * scaled_diff * SQRT_2 - deriv_2 
                * sigma_dbl * SQRT_2 
                * (-SQRT_2 * 0.5 * (-lambda_dbl + scaled_diff * SQRT_2 
                                    / sigma_dbl)
                   - SQRT_2 * lambda_dbl)) 
            / ccdf_;
        if (!is_constant_struct<T_inv_scale>::value)
          operands_and_partials.d_x4[n] -= exp(0.5 * v_sq - u) 
            * (SQRT_2 / sqrt_pi * 0.5 * sigma_dbl 
               * exp(-(v / SQRT_2 - scaled_diff) * (v / SQRT_2 - scaled_diff)) 
               - (v * sigma_dbl + mu_dbl - y_dbl) * erf_calc2) 
            / ccdf_;
      }

      return operands_and_partials.to_var(ccdf_log,y,mu,sigma,lambda);
    }
  }
}
#endif



