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Stan Math Library
5.1.0
Automatic Differentiation
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inline |
Returns a squared exponential kernel.
This function is for the cross covariance matrix needed to compute posterior predictive density.
| T_x1 | type of first std::vector of scalars |
| T_x2 | type of second std::vector of scalars This function assumes each element of x1 and x2 are the same size. |
| T_sigma | type of sigma |
| T_l | type of of length scale |
| x1 | std::vector of elements that can be used in square distance |
| x2 | std::vector of elements that can be used in square distance |
| sigma | standard deviation |
| length_scale | length scale |
| std::domain_error | if sigma <= 0, l <= 0, or x is nan or infinite |
Definition at line 214 of file gp_exp_quad_cov.hpp.