pymc.gp.cov.ScaledCov

class pymc.gp.cov.ScaledCov(input_dim, cov_func, scaling_func, args=None, active_dims=None)

Construct a kernel by multiplying a base kernel with a scaling function defined using PyTensor. The scaling function is non-negative, and can be parameterized.

\[k(x, x') = \phi(x) k_{\text{base}}(x, x') \phi(x')\]

Parameters:

cov_func: Covariance

Base kernel or covariance function

scaling_func: callable

PyTensor function of X and additional optional arguments.

args: optional, tuple or list of scalars or PyMC variables

Additional inputs (besides X or Xs) to lengthscale_func.

Methods

ScaledCov.__init__(input_dim, cov_func, ...)
ScaledCov.diag(X)
ScaledCov.full(X[, Xs])

Attributes

n_dims

The dimensionality of the input, as taken from the active_dims.