pymc.gp.MarginalKron.marginal_likelihood

MarginalKron.marginal_likelihood(name, Xs, y, sigma, is_observed=True, **kwargs)

Returns the marginal likelihood distribution, given the input locations cartesian(*Xs) and the data y.

Parameters:

namestr

Name of the random variable

Xslist of array_like

Function input values for each covariance function. Each entry must be passable to its respective covariance without error. The total covariance function is measured on the full grid cartesian(*Xs).

yarray_like

Data that is the sum of the function with the GP prior and Gaussian noise. Must have shape (n, ).

sigmafloat, Variable

Standard deviation of the white Gaussian noise.

is_observedbool, default True

Deprecated. Whether to set y as an observed variable in the model.

**kwargs

Extra keyword arguments that are passed to KroneckerNormal distribution constructor.