1 #ifndef STAN_MATH_PRIM_MAT_FUN_COV_EXP_QUAD_HPP
2 #define STAN_MATH_PRIM_MAT_FUN_COV_EXP_QUAD_HPP
31 template<
typename T_x,
typename T_sigma,
typename T_l>
33 Eigen::Matrix<typename stan::return_type<T_x, T_sigma, T_l>::type,
34 Eigen::Dynamic, Eigen::Dynamic>
41 for (
size_t n = 0; n < x.size(); n++)
44 Eigen::Matrix<typename stan::return_type<T_x, T_sigma, T_l>::type,
45 Eigen::Dynamic, Eigen::Dynamic>
46 cov(x.size(), x.size());
51 T_sigma sigma_sq =
square(sigma);
52 T_l neg_half_inv_l_sq = - 0.5 /
square(l);
54 for (
size_t i = 0; i < x.size(); ++i) {
56 for (
size_t j = i + 1; j < x.size(); ++j) {
59 cov(j, i) = cov(i, j);
81 template<
typename T_x1,
typename T_x2,
typename T_sigma,
typename T_l>
83 Eigen::Matrix<typename stan::return_type<T_x1, T_x2, T_sigma, T_l>::type,
84 Eigen::Dynamic, Eigen::Dynamic>
86 const std::vector<T_x2>& x2,
92 for (
size_t n = 0; n < x1.size(); n++)
94 for (
size_t n = 0; n < x2.size(); n++)
97 Eigen::Matrix<typename stan::return_type<T_x1, T_x2, T_sigma, T_l>::type,
98 Eigen::Dynamic, Eigen::Dynamic>
99 cov(x1.size(), x2.size());
100 if (x1.size() == 0 || x2.size() == 0)
103 T_sigma sigma_sq =
square(sigma);
104 T_l neg_half_inv_l_sq = - 0.5 /
square(l);
106 for (
size_t i = 0; i < x1.size(); ++i) {
107 for (
size_t j = 0; j < x2.size(); ++j) {
109 * neg_half_inv_l_sq);
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
Eigen::Matrix< typename stan::return_type< T_x, T_sigma, T_l >::type, Eigen::Dynamic, Eigen::Dynamic > cov_exp_quad(const std::vector< T_x > &x, T_sigma &sigma, T_l &l)
Returns a squared exponential kernel.
fvar< T > square(const fvar< T > &x)
fvar< T > squared_distance(const Eigen::Matrix< fvar< T >, R, C > &v1, const Eigen::Matrix< double, R, C > &v2)
Returns the squared distance between the specified vectors of the same dimensions.
fvar< T > exp(const fvar< T > &x)
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.