unblocked_cholesky_lambda()

template<typename T1 , typename T2 , typename T3 >

auto stan::math::internal::unblocked_cholesky_lambda ( T1 &  L_A, T2 &  L, T3 &  A  )

inline

Reverse mode differentiation algorithm reference:

Mike Giles. An extended collection of matrix derivative results for forward and reverse mode AD. Jan. 2008.

Note algorithm as laid out in Giles is row-major, so Eigen::Matrices are explicitly storage order RowMajor, whereas Eigen defaults to ColumnMajor. Also note algorithm starts by calculating the adjoint for A(M_ - 1, M_ - 1), hence pos on line 94 is decremented to start at pos = M_ * (M_ + 1) / 2.

Definition at line 47 of file cholesky_decompose.hpp.