bayespy.inference.vmp.nodes.beta.BetaDistribution¶

class bayespy.inference.vmp.nodes.beta.BetaDistribution[source]¶

Class for the VMP formulas of beta variables.

Although the realizations are scalars (probability p), the moments is a two-dimensional vector: [log(p), log(1-p)].

Methods

`__init__`()
`compute_cgf_from_parents`(u_alpha)	Compute $\mathrm{E}_{q(p)}[g(p)]$
`compute_fixed_moments_and_f`(p[, mask])	Compute the moments and $f(x)$ for a fixed value.
`compute_gradient`(g, u, phi)	Compute the moments and $g(\phi)$ .
`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, ...)	Compute the message to a parent node.
`compute_moments_and_cgf`(phi[, mask])	Compute the moments and $g(\phi)$ .
`compute_phi_from_parents`(u_alpha[, 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.
`squeeze`(axis)	Squeeze a plate axis from the distribution

BayesPy