I’ve fit a GLM to some data I have and would now like to same the posterior predictive distribution conditioned on some covariates. This would be equivalent to me predicting on new data.
Here is some code:
fml = ‘n_affected ~ success’
with pm.Model() as model: pm.glm.GLM.from_formula(formula=fml, data=df, family=pm.glm.families.NegativeBinomial()) trace = pm.sample(5000, tune = 2000)
success is a binary variable, and I am interested in sampling when
success==1. Given I have set up my GLM in this manner, how can I sample from the posterior conditioned so that success == 1?