Predictions for specific values when using model averaging


#1

Hello,

After averaging three models (see example http://docs.pymc.io/notebooks/model_averaging.html), I am generating predictions using this code:

ppc_w = pm.sample_ppc_w(traces, 1000, models,
                        weights=comp.weight.sort_index(ascending=True),
                        progressbar=False)

I would like to create counterfactual predictions based on specific values (data), but there is no data argument in the sample_ppc_w function.

Any ideas or suggestions on how to do it??


#2

If you are trying to generate prediction conditioned on some specific input/data, you should set your input as theano.shared variable, and set the new value for prediction before you do pm.sample_ppc_w or pm.sample_ppc. There is an example here:
http://docs.pymc.io/notebooks/posterior_predictive.html#Prediction


#3

Cool, thanks!