Automatic Differentiation
 
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multi_gp_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_MULTI_GP_LOG_HPP
2#define STAN_MATH_PRIM_PROB_MULTI_GP_LOG_HPP
3
7
8namespace stan {
9namespace math {
10
32template <bool propto, typename T_y, typename T_covar, typename T_w>
34 const T_covar& Sigma,
35 const T_w& w) {
36 return multi_gp_lpdf<propto>(y, Sigma, w);
37}
38
42template <typename T_y, typename T_covar, typename T_w>
44 const T_covar& Sigma,
45 const T_w& w) {
46 return multi_gp_lpdf<>(y, Sigma, w);
47}
48
49} // namespace math
50} // namespace stan
51#endif
return_type_t< T_y, T_covar, T_w > multi_gp_log(const T_y &y, const T_covar &Sigma, const T_w &w)
The log of a multivariate Gaussian Process for the given y, Sigma, and w.
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9