gp_matern32_cov() [4/6]

template<typename T_x , typename T_s , typename T_l >

Eigen::Matrix< return_type_t< T_x, T_s, T_l >, Eigen::Dynamic, Eigen::Dynamic > stan::math::gp_matern32_cov ( const std::vector< Eigen::Matrix< T_x, -1, 1 > > &  x, const T_s &  sigma, const std::vector< T_l > &  length_scale  )

inline

Returns a Matern 3/2 covariance matrix.

\[ k(x, x') = \sigma^2(1 + \sqrt{3} \sqrt{\sum_{k=1}^{K}\frac{d(x, x')^2}{l_k^2}}) exp(-\sqrt{3}\sqrt{\sum_{k=1}^{K}\frac{d(x, x')^2}{l_k^2}}) \]

where \(d(x, x')\) is the Euclidean distance.

Template Parameters

T_x	type for each scalar
T_s	type of element of parameter sigma
T_l	type of each length scale parameter

Parameters

x	std::vector of Eigen vectors of scalars.
length_scale	std::vector of length scales
sigma	standard deviation that can be used in stan::math::square

Exceptions

std::domain

error if sigma <= 0, l <= 0, or x is nan or inf

Definition at line 109 of file gp_matern32_cov.hpp.