bayespy.inference.vmp.nodes.gaussian_markov_chain.VaryingGaussianMarkovChainDistribution

class bayespy.inference.vmp.nodes.gaussian_markov_chain.VaryingGaussianMarkovChainDistribution(N, D)[source]

Sub-classes implement distribution specific computations.

__init__(N, D)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(N, D)

Initialize self.

compute_cgf_from_parents(u_mu, u_Lambda, …)

Compute CGF using the moments of the parents.

compute_fixed_moments_and_f(x[, mask])

Compute u(x) and f(x) for given x.

compute_gradient(g, u, phi)

Compute the standard gradient with respect to the natural parameters.

compute_logpdf(u, phi, g, f, ndims)

Compute E[log p(X)] given E[u], E[phi], E[g] and E[f].

compute_message_to_parent(parent, index, u, …)

Compute a message to a parent.

compute_moments_and_cgf(phi[, mask])

Compute the moments and the cumulant-generating function.

compute_phi_from_parents(u_mu, u_Lambda, …)

Compute the natural parameters using parents’ moments.

compute_rotation_bound(u, u_mu_Lambda, u_A_V, R)

compute_weights_to_parent(index, weights)

Maps the mask to the plates of a parent.

plates_from_parent(index, plates)

Compute the plates using information of a parent node.

plates_to_parent(index, plates)

Computes the plates of this node with respect to a parent.

random(*params[, plates])

Draw a random sample from the distribution.

rotate(u, phi, R[, inv, logdet])

squeeze(axis)

Squeeze a plate axis from the distribution