bayespy.nodes.GaussianWishart¶

class bayespy.nodes.GaussianWishart(*args, **kwargs)[source]

Node for Gaussian-Wishart random variables.

The prior:

The posterior approximation has the same Gaussian-Wishart form.

Currently, supports only vector variables.

__init__(*args, **kwargs)

Methods

 __init__(*args, **kwargs) add_plate_axis(to_plate) broadcasting_multiplier(*args) delete() Delete this node and the children get_gradient(rg) Computes gradient with respect to the natural parameters. get_mask() get_moments() get_parameters() Return parameters of the VB distribution. get_pdf_nodes() get_riemannian_gradient() Computes the Riemannian/natural gradient. get_shape(ind) has_plotter() Return True if the node has a plotter initialize_from_parameters(*args) initialize_from_prior() initialize_from_random() Set the variable to a random sample from the current distribution. initialize_from_value(x, *args) load(filename) logpdf(X[, mask]) Compute the log probability density function Q(X) of this node. lower_bound_contribution([gradient, …]) Compute E[ log p(X|parents) - log q(X) ] lowerbound() move_plates(from_plate, to_plate) observe(x, *args[, mask]) Fix moments, compute f and propagate mask. pdf(X[, mask]) Compute the probability density function of this node. plot([fig]) Plot the node distribution using the plotter of the node random() Draw a random sample from the distribution. save(filename) set_parameters(x) Set the parameters of the VB distribution. set_plotter(plotter) show() Print the distribution using standard parameterization. unobserve() update([annealing])

Attributes

 dims plates plates_multiplier Plate multiplier is applied to messages to parents