Given a list of UPArrays, y_upas, we can find total expectation/variance as:
μs = np.stack([y.μ for y in y_upas])
σ2s = np.stack([y.σ2 for y in y_upas])
total_upa = gmb.uparray('y',
μ = μs.mean(0),
σ2 = μs.var(0) + σ2s.mean(0),
stdzr=stdzr
)
Implement as something like
gmb.uparray.total(y_upas)
Where name and stdzr are inferred from, e.g., the first upa in the list.
Given a list of UPArrays,
y_upas, we can find total expectation/variance as:Implement as something like
Where name and
stdzrare inferred from, e.g., the first upa in the list.