Hi all! I’m working on a model with an ordered categorical predictor (E below). So, the associated parameter is incrementally added to the linear model: when E==0, delta_e = 0; when E==1, delta_e = 0 + delta_e1; when E==2, delta_e = 0 + delta_e1 + delta_e2, etc. In code: with pm.Model() as m: …

Would this work? delta = pm.Dirichlet("delta", np.repeat(2., 7), shape=7) delta_j = tt.concatenate([tt.zeros(1), delta]) delta_j_cumulative = tt.cumsum(delta_j) phi = bE * delta_j_cumulative[E+1] + bA * A

How to vectorize indexing of variable for pm.math.sum?

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junpenglao April 12, 2020, 7:33am 2

Try computing the cumsum first, and index to the resulting cumsum matrix.

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How to vectorize indexing of variable for pm.math.sum?

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