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In the (normal) case of StanModel.sampling(), a StanFit4Model obj is returned, which has a .extract() function that can be used to extract the parameter values. (This is the usual case for running hBayesDM models, with vb=False.)
However, when running with vb=True, the pystan function that is used - StanModel.vb() - returns a Dict obj (not the StanFit4Model obj as in the usual case of using StanModel.sampling()).
Therefore, a different process of proper code needs to be written to handle the case for when the variational Bayesian method is requested by the user, for the Python hbayesdm package.
(I.e. Currently, the variational Bayesian analysis functionality is not supported in the Python package.)
The text was updated successfully, but these errors were encountered:
In the (normal) case of
StanModel.sampling()
, aStanFit4Model
obj is returned, which has a.extract()
function that can be used to extract the parameter values. (This is the usual case for running hBayesDM models, withvb=False
.)However, when running with
vb=True
, the pystan function that is used -StanModel.vb()
- returns aDict
obj (not theStanFit4Model
obj as in the usual case of usingStanModel.sampling()
).Therefore, a different process of proper code needs to be written to handle the case for when the variational Bayesian method is requested by the user, for the Python
hbayesdm
package.(I.e. Currently, the variational Bayesian analysis functionality is not supported in the Python package.)
The text was updated successfully, but these errors were encountered: