uniform_lccdf.hpp

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#ifndef STAN_MATH_PRIM_PROB_UNIFORM_LCCDF_HPP
#define STAN_MATH_PRIM_PROB_UNIFORM_LCCDF_HPP
 
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/fun/as_array_or_scalar.hpp>
#include <stan/math/prim/fun/as_value_column_array_or_scalar.hpp>
#include <stan/math/prim/fun/constants.hpp>
#include <stan/math/prim/fun/log.hpp>
#include <stan/math/prim/fun/max_size.hpp>
#include <stan/math/prim/fun/promote_scalar.hpp>
#include <stan/math/prim/fun/size_zero.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/value_of.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
#include <cmath>
 
namespace stan {
namespace math {
 
template <typename T_y, typename T_low, typename T_high,
          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<
              T_y, T_low, T_high>* = nullptr>
inline return_type_t<T_y, T_low, T_high> uniform_lccdf(const T_y& y,
                                                       const T_low& alpha,
                                                       const T_high& beta) {
  using T_partials_return = partials_return_t<T_y, T_low, T_high>;
  using T_y_ref = ref_type_if_not_constant_t<T_y>;
  using T_alpha_ref = ref_type_if_not_constant_t<T_low>;
  using T_beta_ref = ref_type_if_not_constant_t<T_high>;
  static constexpr const char* function = "uniform_lccdf";
  check_consistent_sizes(function, "Random variable", y,
                         "Lower bound parameter", alpha,
                         "Upper bound parameter", beta);
 
  T_y_ref y_ref = y;
  T_alpha_ref alpha_ref = alpha;
  T_beta_ref beta_ref = beta;
 
  decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
  decltype(auto) alpha_val = to_ref(as_value_column_array_or_scalar(alpha_ref));
  decltype(auto) beta_val = to_ref(as_value_column_array_or_scalar(beta_ref));
 
  check_not_nan(function, "Random variable", y_val);
  check_finite(function, "Lower bound parameter", alpha_val);
  check_finite(function, "Upper bound parameter", beta_val);
  check_greater(function, "Upper bound parameter", beta_val, alpha_val);
 
  if (size_zero(y, alpha, beta)) {
    return 0;
  }
 
  if (sum(promote_scalar<int>(y_val < alpha_val))
      || sum(promote_scalar<int>(beta_val < y_val))) {
    return 0;
  }
 
  auto ops_partials = make_partials_propagator(y_ref, alpha_ref, beta_ref);
 
  const auto& b_minus_a
      = to_ref_if<is_any_autodiff_v<T_y, T_low, T_high>>(beta_val - alpha_val);
  const auto& ccdf_log_n = to_ref_if<is_any_autodiff_v<T_y, T_low, T_high>>(
      1 - (y_val - alpha_val) / b_minus_a);
 
  T_partials_return ccdf_log = sum(log(ccdf_log_n));
 
  if constexpr (is_autodiff_v<T_y>) {
    partials<0>(ops_partials) = inv(-b_minus_a * ccdf_log_n);
  }
  if constexpr (is_any_autodiff_v<T_low, T_high>) {
    const auto& rep_deriv
        = to_ref_if<(is_autodiff_v<T_low> && is_autodiff_v<T_high>)>(
            inv(b_minus_a * b_minus_a * ccdf_log_n));
    if constexpr (is_autodiff_v<T_low>) {
      partials<1>(ops_partials) = (beta_val - y_val) * rep_deriv;
    }
    if constexpr (is_autodiff_v<T_high>) {
      partials<2>(ops_partials) = (y_val - alpha_val) * rep_deriv;
    }
  }
  return ops_partials.build(ccdf_log);
}
 
}  // namespace math
}  // namespace stan
#endif