#ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LPDF_HPP
#define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LPDF_HPP

#include <stan/math/prim/mat/err/check_ldlt_factor.hpp>
#include <stan/math/prim/mat/err/check_symmetric.hpp>
#include <stan/math/prim/mat/fun/trace_inv_quad_form_ldlt.hpp>
#include <stan/math/prim/mat/fun/log_determinant_ldlt.hpp>
#include <stan/math/prim/mat/meta/vector_seq_view.hpp>
#include <stan/math/prim/scal/err/check_size_match.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.hpp>
#include <stan/math/prim/scal/fun/constants.hpp>
#include <stan/math/prim/scal/meta/return_type.hpp>
#include <stan/math/prim/scal/meta/max_size_mvt.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>
#include <boost/random/normal_distribution.hpp>
#include <boost/random/variate_generator.hpp>

namespace stan {
namespace math {

template <bool propto, typename T_y, typename T_loc, typename T_covar>
typename return_type<T_y, T_loc, T_covar>::type multi_normal_lpdf(
    const T_y& y, const T_loc& mu, const T_covar& Sigma) {
  static const char* function = "multi_normal_lpdf";
  typedef typename scalar_type<T_covar>::type T_covar_elem;
  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
  lp_type lp(0.0);

  using Eigen::Dynamic;

  check_positive(function, "Covariance matrix rows", Sigma.rows());
  check_symmetric(function, "Covariance matrix", Sigma);

  LDLT_factor<T_covar_elem, Dynamic, Dynamic> ldlt_Sigma(Sigma);
  check_ldlt_factor(function, "LDLT_Factor of covariance parameter",
                    ldlt_Sigma);

  vector_seq_view<T_y> y_vec(y);
  vector_seq_view<T_loc> mu_vec(mu);
  size_t size_vec = max_size_mvt(y, mu);

  int size_y = y_vec[0].size();
  int size_mu = mu_vec[0].size();
  if (size_vec > 1) {
    int size_y_old = size_y;
    int size_y_new;
    for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
      int size_y_new = y_vec[i].size();
      check_size_match(function,
                       "Size of one of the vectors of "
                       "the random variable",
                       size_y_new,
                       "Size of another vector of the "
                       "random variable",
                       size_y_old);
      size_y_old = size_y_new;
    }
    int size_mu_old = size_mu;
    int size_mu_new;
    for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
      int size_mu_new = mu_vec[i].size();
      check_size_match(function,
                       "Size of one of the vectors of "
                       "the location variable",
                       size_mu_new,
                       "Size of another vector of the "
                       "location variable",
                       size_mu_old);
      size_mu_old = size_mu_new;
    }
    (void)size_y_old;
    (void)size_y_new;
    (void)size_mu_old;
    (void)size_mu_new;
  }

  check_size_match(function, "Size of random variable", size_y,
                   "size of location parameter", size_mu);
  check_size_match(function, "Size of random variable", size_y,
                   "rows of covariance parameter", Sigma.rows());
  check_size_match(function, "Size of random variable", size_y,
                   "columns of covariance parameter", Sigma.cols());

  for (size_t i = 0; i < size_vec; i++) {
    check_finite(function, "Location parameter", mu_vec[i]);
    check_not_nan(function, "Random variable", y_vec[i]);
  }

  if (size_y == 0)
    return lp;

  if (include_summand<propto>::value)
    lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;

  if (include_summand<propto, T_covar_elem>::value)
    lp -= 0.5 * log_determinant_ldlt(ldlt_Sigma) * size_vec;

  if (include_summand<propto, T_y, T_loc, T_covar_elem>::value) {
    lp_type sum_lp_vec(0.0);
    for (size_t i = 0; i < size_vec; i++) {
      Eigen::Matrix<typename return_type<T_y, T_loc>::type, Dynamic, 1>
          y_minus_mu(size_y);
      for (int j = 0; j < size_y; j++)
        y_minus_mu(j) = y_vec[i](j) - mu_vec[i](j);
      sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_minus_mu);
    }
    lp -= 0.5 * sum_lp_vec;
  }
  return lp;
}

template <typename T_y, typename T_loc, typename T_covar>
inline typename return_type<T_y, T_loc, T_covar>::type multi_normal_lpdf(
    const T_y& y, const T_loc& mu, const T_covar& Sigma) {
  return multi_normal_lpdf<false>(y, mu, Sigma);
}

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