<commit_before>#ifndef STAN_MATH_PRIM_PROB_GAMMA_LCDF_HPP
#define STAN_MATH_PRIM_PROB_GAMMA_LCDF_HPP

#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/digamma.hpp>
#include <stan/math/prim/fun/exp.hpp>
#include <stan/math/prim/fun/gamma_p.hpp>
#include <stan/math/prim/fun/grad_reg_lower_inc_gamma.hpp>
#include <stan/math/prim/fun/log.hpp>
#include <stan/math/prim/fun/max_size.hpp>
#include <stan/math/prim/fun/scalar_seq_view.hpp>
#include <stan/math/prim/fun/size.hpp>
#include <stan/math/prim/fun/size_zero.hpp>
#include <stan/math/prim/fun/tgamma.hpp>
#include <stan/math/prim/fun/value_of.hpp>
#include <stan/math/prim/functor/operands_and_partials.hpp>
#include <cmath>

namespace stan {
namespace math {

template <typename T_y, typename T_shape, typename T_inv_scale>
return_type_t<T_y, T_shape, T_inv_scale> gamma_lcdf(const T_y& y,
                                                    const T_shape& alpha,
                                                    const T_inv_scale& beta) {
  using T_partials_return = partials_return_t<T_y, T_shape, T_inv_scale>;
  using std::exp;
  using std::log;
  using std::pow;
  using T_y_ref = ref_type_t<T_y>;
  using T_alpha_ref = ref_type_t<T_shape>;
  using T_beta_ref = ref_type_t<T_inv_scale>;
  static const char* function = "gamma_lcdf";
  check_consistent_sizes(function, "Random variable", y, "Shape parameter",
                         alpha, "Inverse scale parameter", beta);
  T_y_ref y_ref = y;
  T_alpha_ref alpha_ref = alpha;
  T_beta_ref beta_ref = beta;
  check_positive_finite(function, "Shape parameter", alpha_ref);
  check_positive_finite(function, "Inverse scale parameter", beta_ref);
  check_nonnegative(function, "Random variable", y_ref);

  if (size_zero(y, alpha, beta)) {
    return 0;
  }

  T_partials_return P(0.0);
  operands_and_partials<T_y_ref, T_alpha_ref, T_beta_ref> ops_partials(
      y_ref, alpha_ref, beta_ref);

  scalar_seq_view<T_y_ref> y_vec(y_ref);
  scalar_seq_view<T_alpha_ref> alpha_vec(alpha_ref);
  scalar_seq_view<T_beta_ref> beta_vec(beta_ref);
  size_t N = max_size(y, alpha, beta);

  // Explicit return for extreme values
  // The gradients are technically ill-defined, but treated as zero
  for (size_t i = 0; i < stan::math::size(y); i++) {
    if (y_vec.val(i) == 0) {
      return ops_partials.build(negative_infinity());
    }
  }

  VectorBuilder<!is_constant_all<T_shape>::value, T_partials_return, T_shape>
      gamma_vec(math::size(alpha));
  VectorBuilder<!is_constant_all<T_shape>::value, T_partials_return, T_shape>
      digamma_vec(math::size(alpha));

  if (!is_constant_all<T_shape>::value) {
    for (size_t i = 0; i < stan::math::size(alpha); i++) {
      const T_partials_return alpha_dbl = alpha_vec.val(i);
      gamma_vec[i] = tgamma(alpha_dbl);
      digamma_vec[i] = digamma(alpha_dbl);
    }
  }

  for (size_t n = 0; n < N; n++) {
    // Explicit results for extreme values
    // The gradients are technically ill-defined, but treated as zero
    if (y_vec.val(n) == INFTY) {
      return ops_partials.build(0.0);
    }

    const T_partials_return y_dbl = y_vec.val(n);
    const T_partials_return log_y_dbl = log(y_dbl);
    const T_partials_return alpha_dbl = alpha_vec.val(n);
    const T_partials_return beta_dbl = beta_vec.val(n);
    const T_partials_return log_beta_dbl = log(beta_dbl);
    const T_partials_return beta_y_dbl = beta_dbl * y_dbl;

    const T_partials_return Pn = gamma_p(alpha_dbl, beta_y_dbl);
    const T_partials_return log_Pn = log(Pn);

    P += log_Pn;

    if (!is_constant_all<T_y, T_inv_scale>::value) {
      const T_partials_return d_num
          = (-beta_y_dbl) + (alpha_dbl - 1) * (log_beta_dbl + log_y_dbl);
      const T_partials_return d_den = lgamma(alpha_dbl) + log_Pn;
      const T_partials_return d = exp(d_num - d_den);

      if (!is_constant_all<T_y>::value) {
        ops_partials.edge1_.partials_[n] += beta_dbl * d;
      }
      if (!is_constant_all<T_inv_scale>::value) {
        ops_partials.edge3_.partials_[n] += y_dbl * d;
      }
    }
    if (!is_constant_all<T_shape>::value) {
      ops_partials.edge2_.partials_[n]
          += grad_reg_lower_inc_gamma(alpha_dbl, beta_y_dbl) / Pn;
    }
  }
  return ops_partials.build(P);
}

}  // namespace math
}  // namespace stan
#endif
<commit_msg>Remove unused vars<commit_after>#ifndef STAN_MATH_PRIM_PROB_GAMMA_LCDF_HPP
#define STAN_MATH_PRIM_PROB_GAMMA_LCDF_HPP

#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/digamma.hpp>
#include <stan/math/prim/fun/exp.hpp>
#include <stan/math/prim/fun/gamma_p.hpp>
#include <stan/math/prim/fun/grad_reg_lower_inc_gamma.hpp>
#include <stan/math/prim/fun/log.hpp>
#include <stan/math/prim/fun/max_size.hpp>
#include <stan/math/prim/fun/scalar_seq_view.hpp>
#include <stan/math/prim/fun/size.hpp>
#include <stan/math/prim/fun/size_zero.hpp>
#include <stan/math/prim/fun/tgamma.hpp>
#include <stan/math/prim/fun/value_of.hpp>
#include <stan/math/prim/functor/operands_and_partials.hpp>
#include <cmath>

namespace stan {
namespace math {

template <typename T_y, typename T_shape, typename T_inv_scale>
return_type_t<T_y, T_shape, T_inv_scale> gamma_lcdf(const T_y& y,
                                                    const T_shape& alpha,
                                                    const T_inv_scale& beta) {
  using T_partials_return = partials_return_t<T_y, T_shape, T_inv_scale>;
  using std::exp;
  using std::log;
  using std::pow;
  using T_y_ref = ref_type_t<T_y>;
  using T_alpha_ref = ref_type_t<T_shape>;
  using T_beta_ref = ref_type_t<T_inv_scale>;
  static const char* function = "gamma_lcdf";
  check_consistent_sizes(function, "Random variable", y, "Shape parameter",
                         alpha, "Inverse scale parameter", beta);
  T_y_ref y_ref = y;
  T_alpha_ref alpha_ref = alpha;
  T_beta_ref beta_ref = beta;
  check_positive_finite(function, "Shape parameter", alpha_ref);
  check_positive_finite(function, "Inverse scale parameter", beta_ref);
  check_nonnegative(function, "Random variable", y_ref);

  if (size_zero(y, alpha, beta)) {
    return 0;
  }

  T_partials_return P(0.0);
  operands_and_partials<T_y_ref, T_alpha_ref, T_beta_ref> ops_partials(
      y_ref, alpha_ref, beta_ref);

  scalar_seq_view<T_y_ref> y_vec(y_ref);
  scalar_seq_view<T_alpha_ref> alpha_vec(alpha_ref);
  scalar_seq_view<T_beta_ref> beta_vec(beta_ref);
  size_t N = max_size(y, alpha, beta);

  // Explicit return for extreme values
  // The gradients are technically ill-defined, but treated as zero
  for (size_t i = 0; i < stan::math::size(y); i++) {
    if (y_vec.val(i) == 0) {
      return ops_partials.build(negative_infinity());
    }
  }

  for (size_t n = 0; n < N; n++) {
    // Explicit results for extreme values
    // The gradients are technically ill-defined, but treated as zero
    if (y_vec.val(n) == INFTY) {
      return ops_partials.build(0.0);
    }

    const T_partials_return y_dbl = y_vec.val(n);
    const T_partials_return log_y_dbl = log(y_dbl);
    const T_partials_return alpha_dbl = alpha_vec.val(n);
    const T_partials_return beta_dbl = beta_vec.val(n);
    const T_partials_return log_beta_dbl = log(beta_dbl);
    const T_partials_return beta_y_dbl = beta_dbl * y_dbl;

    const T_partials_return Pn = gamma_p(alpha_dbl, beta_y_dbl);
    const T_partials_return log_Pn = log(Pn);

    P += log_Pn;

    if (!is_constant_all<T_y, T_inv_scale>::value) {
      const T_partials_return d_num
          = (-beta_y_dbl) + (alpha_dbl - 1) * (log_beta_dbl + log_y_dbl);
      const T_partials_return d_den = lgamma(alpha_dbl) + log_Pn;
      const T_partials_return d = exp(d_num - d_den);

      if (!is_constant_all<T_y>::value) {
        ops_partials.edge1_.partials_[n] += beta_dbl * d;
      }
      if (!is_constant_all<T_inv_scale>::value) {
        ops_partials.edge3_.partials_[n] += y_dbl * d;
      }
    }
    if (!is_constant_all<T_shape>::value) {
      ops_partials.edge2_.partials_[n]
          += grad_reg_lower_inc_gamma(alpha_dbl, beta_y_dbl) / Pn;
    }
  }
  return ops_partials.build(P);
}

}  // namespace math
}  // namespace stan
#endif

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