12.6 Exponentiated quadratic covariance functions
These covariance functions have been replaced by those described in:
With magnitude \(\alpha\) and length scale \(l\), the exponentiated quadratic kernel is:
\[ k(x_i, x_j) = \alpha^2 \exp \left(-\dfrac{1}{2\rho^2} \sum_{d=1}^D (x_{i,d} - x_{j,d})^2 \right) \]
matrix cov_exp_quad(row_vectors x, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x.
Available since 2.16, deprecated since 2.20, scheduled for removal in 2.32
matrix cov_exp_quad(vectors x, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x.
Available since 2.16, deprecated since 2.20, scheduled for removal in 2.32
matrix cov_exp_quad(array[] real x, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x.
Available since 2.16, deprecated since 2.20, scheduled for removal in 2.32
matrix cov_exp_quad(row_vectors x1, row_vectors x2, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x1 and
x2.
Available since 2.18, deprecated since 2.20, scheduled for removal in 2.32
matrix cov_exp_quad(vectors x1, vectors x2, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x1 and
x2.
Available since 2.18, deprecated since 2.20, scheduled for removal in 2.32
matrix cov_exp_quad(array[] real x1, array[] real x2, real alpha, real rho)
The covariance matrix with an exponentiated quadratic kernel of x1 and
x2.
Available since 2.18, deprecated since 2.20, scheduled for removal in 2.32