Hey to everybody, I’m about to model the following data (synthetically created) by a simple hierarchical regression model [synthetic_dataset1] Where p=0 means that there is no variable p given for that particular y (as such, p=0 is specified by me and could be any other value). However, the data …

Switch on group rather than missing: with pm.Model() as mod: o_scale = pm.HalfNormal('offset_scale', 0.1) offset = pm.Normal('offset', 0, o_scale) offset_missing = pm.Normal('offset_mis', 0, o_scale) be_scale = pm.HalfNormal('be_scale', 0.1) beta = pm.Normal('beta', 0, be_scale)…

Exclude group inference for single parameter

Questions

rzu512 May 19, 2019, 5:42pm 2

Is it possible to get rid of the data with p = 0 before letting pymc fit the data?

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Exclude group inference for single parameter

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