A follow-on question:
In GLM, the dummy variable encoding automatically drops one value. In other words, if there are n options, it creates n-1 dummy variables.
What’s the best way to achieve this in the general model?
I have a variable defined as:
b = pm.Normal(‘b’, mu=0., sd=0.5, shape=no_dow)
dow stands for “Day of week”.
Is it possible to define this so that:
b[0] = 0
b[1:] = pm.Normal(‘b’, mu=0., sd=0.5, shape=no_dow-1)
Or should I have used something different, like pm.Categorical ? (I’m not familiar with that distribution).