pyhgf.updates.vectorised.continuous.vectorised_continuous_posterior_update_standard#

pyhgf.updates.vectorised.continuous.vectorised_continuous_posterior_update_standard(layer, value_child=None, volatility_child=None, max_posterior_precision=10000000000.0, mean_field_updates=False)[source]#

Apply the standard HGF posterior update: precision first, then the mean.

This is the vectorised equivalent of pyhgf.updates.posterior.continuous.continuous_node_posterior_update().

Parameters:

  • layer (LayerState) – The parent layer’s state (being updated).

  • value_child (ValueChild | None) – The value child, or None.

  • volatility_child (VolatilityChild | None) – The volatility child, or None.

  • max_posterior_precision (float) – Upper bound applied to the posterior precision write.

  • mean_field_updates (bool) – If True, weight the value-coupling messages by the canonical predicted precision instead of the smoothing factors — the original mean-field update (pyhgf.updates.posterior.continuous.continuous_node_posterior_update_mean_field()). The volatility-coupling increment is the same in both schemes.

Returns:

Updated layer state with posterior precision and mean.

Return type:

LayerState