Modeling Weibull Proportional Hazard

I’m looking to create a Bayesian proportional hazard model where the baseline hazard is modeled by a Weibull distribution (or some similar continuous distribution).

I’ve reviewed (and implemented) the cox proportional hazard example here where the baseline hazard is piece wise constant and modeled with a Poisson’s distribution Bayesian Survival Analysis — PyMC3 3.11.5 documentation

I’ve reviewed (and implemented) the accelerated failure Weibull models at

It’s not obvious to me how to put them together. I started down the path of thinking of logs of hazard ratios, but couldn’t quite land how to model this and bring in my measured and censored survival times.

Any advice?

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The question was answered over at bayesian - Weibull Proportional Hazard in pymc - Cross Validated

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