# bayespy.inference.vmp.nodes.gaussian_markov_chain.SwitchingGaussianMarkovChainDistribution¶

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

Sub-classes implement distribution specific computations.

__init__(N, D, K)[source]

Methods

 __init__(N, D, K) 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