class bayespy.inference.vmp.nodes.gaussian.GaussianARDDistribution(shape)[source]

Log probability density function:

\log p(x|\mu, \alpha) = -\frac{1}{2} x^T \mathrm{diag}(\alpha) x + x^T
\mathrm{diag}(\alpha) \mu - \frac{1}{2} \mu^T \mathrm{diag}(\alpha) \mu
+ \frac{1}{2} \sum_i \log \alpha_i - \frac{D}{2} \log(2\pi)

Parent has moments:

    \alpha \circ \mu
    \alpha \circ \mu \circ \mu


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


__init__(shape) Initialize self.
compute_cgf_from_parents(u_mu_alpha) Compute the value of the cumulant generating function.
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_moments_and_cgf(phi[, mask])
compute_phi_from_parents(u_mu_alpha[, mask])
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 Gaussian distribution.