lognormal_lccdf.hpp

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#ifndef STAN_MATH_OPENCL_PRIM_LOGNORMAL_LCCDF_HPP
#define STAN_MATH_OPENCL_PRIM_LOGNORMAL_LCCDF_HPP
#ifdef STAN_OPENCL
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/elt_divide.hpp>
#include <stan/math/prim/fun/elt_multiply.hpp>
#include <stan/math/opencl/kernel_generator.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
 
namespace stan {
namespace math {
 
template <
    typename T_y_cl, typename T_loc_cl, typename T_scale_cl,
    require_all_prim_or_rev_kernel_expression_t<T_y_cl, T_loc_cl,
                                                T_scale_cl>* = nullptr,
    require_any_not_stan_scalar_t<T_y_cl, T_loc_cl, T_scale_cl>* = nullptr>
inline return_type_t<T_y_cl, T_loc_cl, T_scale_cl> lognormal_lccdf(
    const T_y_cl& y, const T_loc_cl& mu, const T_scale_cl& sigma) {
  static constexpr const char* function = "lognormal_lccdf(OpenCL)";
  using T_partials_return = partials_return_t<T_y_cl, T_loc_cl, T_scale_cl>;
  using std::isfinite;
  using std::isnan;
 
  check_consistent_sizes(function, "Random variable", y, "Location parameter",
                         mu, "Scale parameter", sigma);
  const size_t N = max_size(y, mu, sigma);
  if (N == 0) {
    return 0.0;
  }
 
  const auto& y_col = as_column_vector_or_scalar(y);
  const auto& mu_col = as_column_vector_or_scalar(mu);
  const auto& sigma_col = as_column_vector_or_scalar(sigma);
 
  const auto& y_val = value_of(y_col);
  const auto& mu_val = value_of(mu_col);
  const auto& sigma_val = value_of(sigma_col);
 
  auto check_y_nonnegative
      = check_cl(function, "Random variable", y_val, "nonnegative");
  auto y_nonnegative = 0.0 <= y_val;
  auto check_mu_finite
      = check_cl(function, "Location parameter", mu_val, "finite");
  auto mu_finite_expr = isfinite(mu_val);
  auto check_sigma_positive_finite
      = check_cl(function, "Scale parameter", sigma_val, "positive finite");
  auto sigma_positive_finite_expr = 0 < sigma_val && isfinite(sigma_val);
 
  auto any_y_zero = colwise_max(cast<char>(y_val == 0.0));
  auto log_y = log(y_val);
  auto scaled_diff = elt_divide(log_y - mu_val, sigma_val * SQRT_TWO);
  auto erfc_calc = erfc(scaled_diff);
  auto lccdf_expr = colwise_sum(log(erfc_calc));
  auto mu_deriv = elt_divide(SQRT_TWO_OVER_SQRT_PI * exp(-square(scaled_diff)),
                             elt_multiply(sigma_val, erfc_calc));
  auto y_deriv = elt_divide(mu_deriv, -y_val);
  auto sigma_deriv = elt_multiply(mu_deriv, scaled_diff * SQRT_TWO);
 
  matrix_cl<char> any_y_zero_cl;
  matrix_cl<double> lccdf_cl;
  matrix_cl<double> y_deriv_cl;
  matrix_cl<double> mu_deriv_cl;
  matrix_cl<double> sigma_deriv_cl;
 
  results(check_y_nonnegative, check_mu_finite, check_sigma_positive_finite,
          any_y_zero_cl, lccdf_cl, y_deriv_cl, mu_deriv_cl, sigma_deriv_cl)
      = expressions(y_nonnegative, mu_finite_expr, sigma_positive_finite_expr,
                    any_y_zero, lccdf_expr,
                    calc_if<is_autodiff_v<T_y_cl>>(y_deriv),
                    calc_if<is_autodiff_v<T_loc_cl>>(mu_deriv),
                    calc_if<is_autodiff_v<T_scale_cl>>(sigma_deriv));
 
  if (from_matrix_cl(any_y_zero_cl).maxCoeff()) {
    return 0.0;
  }
 
  T_partials_return lccdf = N * LOG_HALF + sum(from_matrix_cl(lccdf_cl));
 
  auto ops_partials = make_partials_propagator(y_col, mu_col, sigma_col);
 
  if constexpr (is_autodiff_v<T_y_cl>) {
    partials<0>(ops_partials) = std::move(y_deriv_cl);
  }
  if constexpr (is_autodiff_v<T_loc_cl>) {
    partials<1>(ops_partials) = std::move(mu_deriv_cl);
  }
  if constexpr (is_autodiff_v<T_scale_cl>) {
    partials<2>(ops_partials) = std::move(sigma_deriv_cl);
  }
  return ops_partials.build(lccdf);
}
 
}  // namespace math
}  // namespace stan
#endif
#endif