Automatic Differentiation
 
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◆ theta_grad()

template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
auto stan::math::laplace_likelihood::internal::theta_grad ( F &&  f,
Theta &&  theta,
Stream *  msgs,
Args &&...  args 
)
inline

Computes theta gradient f wrt theta and args...

Note
If Args contains var types then their adjoints will be calculated as a side effect.
Template Parameters
FA functor with opertor()(Args&&...) returning a scalar
ThetaA class assignable to an Eigen vector type
StreamType of stream for messages.
ArgsType of variadic arguments.
Parameters
fLog likelihood function.
thetaLatent Gaussian model.
msgsStream for messages.
argsVariadic arguments for the likelihood function.

Definition at line 51 of file laplace_likelihood.hpp.