pyhgf.updates.posterior.categorical.categorical_state_update#

pyhgf.updates.posterior.categorical.categorical_state_update(attributes: Dict, node_idx: int, edges: Tuple[AdjacencyLists, ...], **args) → Dict[source]#

Update the categorical input node given an array of binary observations.

This function should be called after the update of the implied binary HGFs. It receives a None as the boolean observations are passed to the binary inputs directly. This update uses the expected probability of the binary input to update an implied Dirichlet distribution.

Parameters:

attributes: The attributes of the probabilistic nodes.
.. note::: “psis” is the value coupling strength. It should have the same length as the volatility parents’ indexes. “volatility_coupling” is the volatility coupling strength. It should have the same length as the volatility parents’ indexes.
node_idx: Pointer to the node that needs to 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 parameters structure.