Automatic Differentiation
 
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◆ gp_exp_quad_cov() [4/7]

template<typename T_x , typename T_sigma , typename T_l >
Eigen::Matrix< return_type_t< T_x, T_sigma, T_l >, Eigen::Dynamic, Eigen::Dynamic > stan::math::gp_exp_quad_cov ( const std::vector< Eigen::Matrix< T_x, -1, 1 > > &  x,
const T_sigma &  sigma,
const std::vector< T_l > &  length_scale 
)
inline

Returns a squared exponential kernel.

Template Parameters
T_xtype for each scalar
T_sigmatype of parameter sigma
T_ltype of each length scale parameter
Parameters
xstd::vector of Eigen vectors of scalars.
sigmamarginal standard deviation or magnitude
length_scalestd::vector length scale
Returns
squared distance
Exceptions
std::domain_errorif sigma <= 0, l <= 0, or x is nan or infinite

Definition at line 166 of file gp_exp_quad_cov.hpp.