1#ifndef STAN_MATH_FWD_FUN_MDIVIDE_LEFT_TRI_LOW_HPP 
    2#define STAN_MATH_FWD_FUN_MDIVIDE_LEFT_TRI_LOW_HPP 
   16template <
typename T1, 
typename T2,
 
   17          require_all_eigen_vt<is_fvar, T1, T2>* = 
nullptr,
 
   18          require_vt_same<T1, T2>* = 
nullptr>
 
   19inline Eigen::Matrix<value_type_t<T1>, T1::RowsAtCompileTime,
 
   20                     T2::ColsAtCompileTime>
 
   23  constexpr int S1 = T1::RowsAtCompileTime;
 
   24  constexpr int C2 = T2::ColsAtCompileTime;
 
   32  Eigen::Matrix<T, S1, S1> val_A(A.rows(), A.cols());
 
   33  Eigen::Matrix<T, S1, S1> deriv_A(A.rows(), A.cols());
 
   37  const Eigen::Ref<const plain_type_t<T2>>& b_ref = b;
 
   38  const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
 
   39  for (
size_type j = 0; j < A.cols(); j++) {
 
   40    for (
size_type i = j; i < A.rows(); i++) {
 
   41      val_A(i, j) = A_ref(i, j).val_;
 
   42      deriv_A(i, j) = A_ref(i, j).d_;
 
   46  Eigen::Matrix<T, S1, C2> inv_A_mult_b = 
mdivide_left(val_A, b_ref.val());
 
   53template <
typename T1, 
typename T2, require_eigen_t<T1>* = 
nullptr,
 
   54          require_vt_same<
double, T1>* = 
nullptr,
 
   55          require_eigen_vt<is_fvar, T2>* = 
nullptr>
 
   56inline Eigen::Matrix<value_type_t<T2>, T1::RowsAtCompileTime,
 
   57                     T2::ColsAtCompileTime>
 
   59  constexpr int S1 = T1::RowsAtCompileTime;
 
   67  Eigen::Matrix<double, S1, S1> val_A(A.rows(), A.cols());
 
   70  const Eigen::Ref<const plain_type_t<T2>>& b_ref = b;
 
   71  const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
 
   72  for (
size_type j = 0; j < A.cols(); j++) {
 
   73    for (
size_type i = j; i < A.rows(); i++) {
 
   74      val_A(i, j) = A_ref(i, j);
 
   82template <
typename T1, 
typename T2, require_eigen_vt<is_fvar, T1>* = 
nullptr,
 
   83          require_eigen_t<T2>* = 
nullptr,
 
   84          require_vt_same<
double, T2>* = 
nullptr>
 
   85inline Eigen::Matrix<value_type_t<T1>, T1::RowsAtCompileTime,
 
   86                     T2::ColsAtCompileTime>
 
   89  constexpr int S1 = T1::RowsAtCompileTime;
 
   90  constexpr int C2 = T2::ColsAtCompileTime;
 
   98  Eigen::Matrix<T, S1, S1> val_A(A.rows(), A.cols());
 
   99  Eigen::Matrix<T, S1, S1> deriv_A(A.rows(), A.cols());
 
  103  const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
 
  104  for (
size_type j = 0; j < A.cols(); j++) {
 
  105    for (
size_type i = j; i < A.rows(); i++) {
 
  106      val_A(i, j) = A_ref(i, j).val_;
 
  107      deriv_A(i, j) = A_ref(i, j).d_;
 
  111  Eigen::Matrix<T, S1, C2> inv_A_mult_b = 
mdivide_left(val_A, b);
 
typename value_type< T >::type value_type_t
Helper function for accessing underlying type.
 
void check_square(const char *function, const char *name, const T_y &y)
Check if the specified matrix is square.
 
void check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Check if the matrices can be multiplied.
 
auto multiply(const Mat1 &m1, const Mat2 &m2)
Return the product of the specified matrices.
 
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double elements.
 
fvar< T > to_fvar(const T &x)
 
Eigen::Matrix< value_type_t< T1 >, T1::RowsAtCompileTime, T2::ColsAtCompileTime > mdivide_left(const T1 &A, const T2 &b)
 
Eigen::Matrix< value_type_t< T1 >, T1::RowsAtCompileTime, T2::ColsAtCompileTime > mdivide_left_tri_low(const T1 &A, const T2 &b)
 
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...