How to use sample_posterior_predictive for out-of-sample prediction with BART?

[y_m]

Hi, yiyi-z.
I’m not team member but I posted similar question so I share the link.

Is using the BART's predict function a correct way to predict new data?

Hello and thank you to all the developers for your continued support. I want to predict new data with a model using BART. So I used the method pm.MutableData() and pass the value to BART like this… data_X = pm.MutableData("df_X", df_X[use_cols]) data_y = pm.MutableData("df_y", df_y[target_cols[0]]) σ = pm.Normal("σ", model_params["Normal"]["σ"]) μ = pmb.BART("μ", data_X, data_y, m=model_params["BART"]["m"], alpha=model_params["BART"]["alpha"]) y = pm.Normal("y", μ, σ, ob…

I hope this post helps you.

so I’m told that BART can’t work with sample_posterior_predictive and aloctavodia, a member of team, suggested me to use “stats.norm”.
(And now I’m searching for how to use stats.norm. if you know how to use and don’t mind to share it, please share it to me and others.)

Thanks.