Automatic Differentiation
 
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trace_quad_form.hpp
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1#ifndef STAN_MATH_FWD_FUN_TRACE_QUAD_FORM_HPP
2#define STAN_MATH_FWD_FUN_TRACE_QUAD_FORM_HPP
3
11
12namespace stan {
13namespace math {
14
15template <typename EigMat1, typename EigMat2,
16 require_all_eigen_t<EigMat1, EigMat2>* = nullptr,
17 require_any_vt_fvar<EigMat1, EigMat2>* = nullptr>
19 const EigMat2& B) {
20 check_square("trace_quad_form", "A", A);
21 check_multiplicable("trace_quad_form", "A", A, "B", B);
22 const auto& B_ref = to_ref(B);
23 return B_ref.cwiseProduct(multiply(A, B_ref)).sum();
24}
25
26} // namespace math
27} // namespace stan
28
29#endif
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
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.
Definition multiply.hpp:18
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:17
return_type_t< EigMat1, EigMat2 > trace_quad_form(const EigMat1 &A, const EigMat2 &B)
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9