bayespy.inference.vmp.nodes.categorical_markov_chain.CategoricalMarkovChainDistribution

class bayespy.inference.vmp.nodes.categorical_markov_chain.CategoricalMarkovChainDistribution(categories, states)[source]

Class for the VMP formulas of categorical Markov chain variables.

__init__(categories, states)[source]

Create VMP formula node for a categorical variable

categories is the total number of categories. states is the length of the chain.

Methods

__init__(categories, states) Create VMP formula node for a categorical variable
compute_cgf_from_parents(u_p0, u_P) Compute \mathrm{E}_{q(p)}[g(p)]
compute_fixed_moments_and_f(x[, mask]) Compute the moments and f(x) for a fixed value.
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 the message to a parent node.
compute_moments_and_cgf(phi[, mask]) Compute the moments and g(\phi).
compute_phi_from_parents(u_p0, u_P[, mask]) Compute the natural parameter vector given parent moments.
compute_weights_to_parent(index, weights) Maps the mask to the plates of a parent.
plates_from_parent(index, plates) Resolve the plate mapping from a parent.
plates_to_parent(index, plates) Resolves the plate mapping to a parent.
random(*phi[, plates]) Draw a random sample from the distribution.