pyhgf.updates.prediction.continuous.continuous_node_prediction#
- pyhgf.updates.prediction.continuous.continuous_node_prediction(attributes: Dict, node_idx: int, edges: Tuple[AdjacencyLists, ...], **args) Dict[source]#
Update the expected mean and expected precision of a continuous node.
- Parameters:
- attributes
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
Pointer to the node that will be updated.
- edges
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:
- attributes
The updated attributes of the probabilistic nodes.
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