pyhgf.updates.prediction.continuous.continuous_node_prediction#

pyhgf.updates.prediction.continuous.continuous_node_prediction(attributes: Dict, time_step: float, 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”).
time_step: The interval between the previous time point and the current time point.
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.