While working through some examples, I am stuck on how to incorporate a matrix of covariates in this example: Prior and Posterior Predictive Checks — PyMC3 3.10.0 documentation mu_pp = (ppc["a"] + ppc["b"] * predictor_scaled[:, None]).T Let’s say that I also generated ppc['covariates'] which is a …

[image] localh: with main_lm_model: lm_trace = pm.sample(draws=1000, step=step, init='jitter+adapt_diag', cores=4, tune=500, # burn in return_inferencedata=…

PyMC3 posterior prediction example; how to incorporate a matrix of betas?

Questions

localh April 15, 2021, 11:19pm 3

Thanks so much, I will dig into these and get more accustom to the pm.Data containers!

Topic		Replies	Views
PyMC3+ArviZ: improve your workflow with labeled coords and dims Sharing doc	20	5877	April 5, 2021
Generating Posterior Predictive Samples Over Forecast Period Questions	13	1267	January 2, 2020
Plot posterior predictive several coordinates Questions	7	1728	September 24, 2020
Create model matrix Questions	7	1518	June 23, 2021
How to predict new values on hold-out data Questions	24	13494	July 22, 2020

PyMC3 posterior prediction example; how to incorporate a matrix of betas?

Related topics