#ifndef STAN_MATH_PRIM_PROB_SCALED_INV_CHI_SQUARE_LPDF_HPP
#define STAN_MATH_PRIM_PROB_SCALED_INV_CHI_SQUARE_LPDF_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/grad_reg_inc_gamma.hpp>
#include <stan/math/prim/fun/lgamma.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/value_of.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
#include <cmath>

namespace stan {
namespace math {

/** \ingroup prob_dists
 * The log of a scaled inverse chi-squared density for y with the
 * specified degrees of freedom parameter and scale parameter.
 *
 \f{eqnarray*}{
 y &\sim& \mbox{\sf{Inv-}}\chi^2(\nu, s^2) \\
 \log (p (y \, |\, \nu, s)) &=& \log \left( \frac{(\nu / 2)^{\nu / 2}}{\Gamma
 (\nu / 2)} s^\nu y^{- (\nu / 2 + 1)} \exp^{-\nu s^2 / (2y)} \right) \\
 &=& \frac{\nu}{2} \log(\frac{\nu}{2}) - \log (\Gamma (\nu / 2)) + \nu \log(s) -
 (\frac{\nu}{2} + 1) \log(y) - \frac{\nu s^2}{2y} \\ & & \mathrm{ where } \; y >
 0 \f}
 *
 * @tparam T_y type of scalar
 * @tparam T_dof type of degrees of freedom
 * @tparam T_Scale type of scale
 * @param y A scalar variable.
 * @param nu Degrees of freedom.
 * @param s Scale parameter.
 * @throw std::domain_error if nu is not greater than 0
 * @throw std::domain_error if s is not greater than 0.
 * @throw std::domain_error if y is not greater than 0.
 */
template <bool propto, typename T_y, typename T_dof, typename T_scale,
          require_all_not_nonscalar_prim_or_rev_kernel_expression_t<
              T_y, T_dof, T_scale>* = nullptr>
inline return_type_t<T_y, T_dof, T_scale> scaled_inv_chi_square_lpdf(
    const T_y& y, const T_dof& nu, const T_scale& s) {
  using T_partials_return = partials_return_t<T_y, T_dof, T_scale>;
  using std::log;
  using T_y_ref = ref_type_t<T_y>;
  using T_nu_ref = ref_type_t<T_dof>;
  using T_s_ref = ref_type_t<T_scale>;
  static constexpr const char* function = "scaled_inv_chi_square_lpdf";
  check_consistent_sizes(function, "Random variable", y,
                         "Degrees of freedom parameter", nu, "Scale parameter",
                         s);
  T_y_ref y_ref = y;
  T_nu_ref nu_ref = nu;
  T_s_ref s_ref = s;
  check_not_nan(function, "Random variable", y_ref);
  check_positive_finite(function, "Degrees of freedom parameter", nu_ref);
  check_positive_finite(function, "Scale parameter", s_ref);

  if (size_zero(y, nu, s)) {
    return 0;
  }
  if constexpr (!include_summand<propto, T_y, T_dof, T_scale>::value) {
    return 0;
  }

  T_partials_return logp(0);
  auto ops_partials = make_partials_propagator(y_ref, nu_ref, s_ref);

  scalar_seq_view<T_y_ref> y_vec(y_ref);
  scalar_seq_view<T_nu_ref> nu_vec(nu_ref);
  scalar_seq_view<T_s_ref> s_vec(s_ref);
  size_t N = max_size(y, nu, s);

  for (size_t n = 0; n < N; n++) {
    if (y_vec.val(n) <= 0) {
      return LOG_ZERO;
    }
  }

  VectorBuilder<include_summand<propto, T_dof, T_y, T_scale>::value,
                T_partials_return, T_dof>
      half_nu(math::size(nu));
  for (size_t i = 0; i < stan::math::size(nu); i++) {
    if constexpr (include_summand<propto, T_dof, T_y, T_scale>::value) {
      half_nu[i] = 0.5 * nu_vec.val(i);
    }
  }

  VectorBuilder<include_summand<propto, T_dof, T_y>::value, T_partials_return,
                T_y>
      log_y(math::size(y));
  for (size_t i = 0; i < stan::math::size(y); i++) {
    if constexpr (include_summand<propto, T_dof, T_y>::value) {
      log_y[i] = log(y_vec.val(i));
    }
  }

  VectorBuilder<include_summand<propto, T_dof, T_y, T_scale>::value,
                T_partials_return, T_y>
      inv_y(math::size(y));
  for (size_t i = 0; i < stan::math::size(y); i++) {
    if constexpr (include_summand<propto, T_dof, T_y, T_scale>::value) {
      inv_y[i] = 1.0 / y_vec.val(i);
    }
  }

  VectorBuilder<include_summand<propto, T_dof, T_scale>::value,
                T_partials_return, T_scale>
      log_s(math::size(s));
  for (size_t i = 0; i < stan::math::size(s); i++) {
    if constexpr (include_summand<propto, T_dof, T_scale>::value) {
      log_s[i] = log(s_vec.val(i));
    }
  }

  VectorBuilder<include_summand<propto, T_dof>::value, T_partials_return, T_dof>
      log_half_nu(math::size(nu));
  VectorBuilder<include_summand<propto, T_dof>::value, T_partials_return, T_dof>
      lgamma_half_nu(math::size(nu));
  VectorBuilder<is_autodiff_v<T_dof>, T_partials_return, T_dof>
      digamma_half_nu_over_two(math::size(nu));
  for (size_t i = 0; i < stan::math::size(nu); i++) {
    if constexpr (include_summand<propto, T_dof>::value) {
      lgamma_half_nu[i] = lgamma(half_nu[i]);
    }
    if constexpr (include_summand<propto, T_dof>::value) {
      log_half_nu[i] = log(half_nu[i]);
    }
    if constexpr (is_autodiff_v<T_dof>) {
      digamma_half_nu_over_two[i] = digamma(half_nu[i]) * 0.5;
    }
  }

  for (size_t n = 0; n < N; n++) {
    const T_partials_return s_dbl = s_vec.val(n);
    const T_partials_return nu_dbl = nu_vec.val(n);
    if constexpr (include_summand<propto, T_dof>::value) {
      logp += half_nu[n] * log_half_nu[n] - lgamma_half_nu[n];
    }
    if constexpr (include_summand<propto, T_dof, T_scale>::value) {
      logp += nu_dbl * log_s[n];
    }
    if constexpr (include_summand<propto, T_dof, T_y>::value) {
      logp -= (half_nu[n] + 1.0) * log_y[n];
    }
    if constexpr (include_summand<propto, T_dof, T_y, T_scale>::value) {
      logp -= half_nu[n] * s_dbl * s_dbl * inv_y[n];
    }

    if constexpr (is_autodiff_v<T_y>) {
      partials<0>(ops_partials)[n]
          += -(half_nu[n] + 1.0) * inv_y[n]
             + half_nu[n] * s_dbl * s_dbl * inv_y[n] * inv_y[n];
    }
    if constexpr (is_autodiff_v<T_dof>) {
      partials<1>(ops_partials)[n]
          += 0.5 * log_half_nu[n] + 0.5 - digamma_half_nu_over_two[n] + log_s[n]
             - 0.5 * log_y[n] - 0.5 * s_dbl * s_dbl * inv_y[n];
    }
    if constexpr (is_autodiff_v<T_scale>) {
      partials<2>(ops_partials)[n]
          += nu_dbl / s_dbl - nu_dbl * inv_y[n] * s_dbl;
    }
  }
  return ops_partials.build(logp);
}

template <typename T_y, typename T_dof, typename T_scale>
inline return_type_t<T_y, T_dof, T_scale> scaled_inv_chi_square_lpdf(
    const T_y& y, const T_dof& nu, const T_scale& s) {
  return scaled_inv_chi_square_lpdf<false>(y, nu, s);
}

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