pyhgf.updates.prediction.continuous.continuous_node_prediction#

pyhgf.updates.prediction.continuous.continuous_node_prediction(attributes, node_idx, edges, **args)[source]#

Update the expected mean and expected precision of a continuous node [1].

The precision prediction follows the improved (piHGF) scheme, which marginalises over the parents’ variational Gaussians instead of treating them as point estimates. See predict_precision() for the precise formula and its two additional variance terms (volatility-coupling moment-generating- function term and value-coupling Laplace term).

Note

The parameter structure also incorporates the value and volatility coupling strength with children and parents (i.e. “value_coupling_parents”, “value_coupling_children”, “volatility_coupling_parents”, “volatility_coupling_children”).

Parameters:

attributes (dict) – The attributes of the probabilistic nodes.
node_idx (int) – Pointer to the node that will be updated.
edges (tuple[AdjacencyLists, ...]) – The edges of the probabilistic nodes as a tuple of pyhgf.typing.AdjacencyLists. The tuple has the same length as the node number. For each node, the index lists the value and volatility parents and children.

Returns:

The updated attributes of the probabilistic nodes.

Return type:

attributes