pyhgf.updates.prediction.continuous.continuous_node_prediction

pyhgf.updates.prediction.continuous.continuous_node_prediction(attributes, node_idx, edges, **args)

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

Parameters:

• attributes (dict) – The attributes of the probabilistic nodes.

• 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”).

• 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.Indexes. 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

See also

update_continuous_input_parents, update_binary_input_parents

References

[1]

Weber, L. A., Waade, P. T., Legrand, N., Møller, A. H., Stephan, K. E., & Mathys, C. (2023). The generalized Hierarchical Gaussian Filter (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2305.10937