gp_exponential_cov() [1/6]

template<typename T1 , typename T2 , typename T3 , require_all_kernel_expressions_and_none_scalar_t< T1 > * = nullptr, require_all_arithmetic_t< T2, T3 > * = nullptr>

matrix_cl< return_type_t< T1, T2, T3 > > stan::math::gp_exponential_cov ( const T1 &  x, const T2  sigma, const T3  length_scale  )

inline

Matern exponential kernel on the GPU.

Squared exponential kernel on the GPU.

Template Parameters

T1	Type of the matrix
T2	Type of sigma
T3	Type of length_scale

Parameters

x	input vector or matrix
sigma	standard deviation
length_scale	length scale

Returns

dot product covariance matrix that is positive semi-definite

Template Parameters

T1	Type of the matrix
T2	Type of sigma
T3	Type of length_scale

Parameters

x	input vector or matrix
sigma	standard deviation
length_scale	length scale

Returns

Squared distance between elements of x.

Definition at line 29 of file gp_exponential_cov.hpp.