I want to have a normal distribution with upper and lower bound. the code: model = pm.Model() with model: x1=pm.math.maximum(pm.math.minimum(pm.Normal('s',mu=0.45,sd=0.15), 0.7),0.4) x1.name="x1" step=pm.HamiltonianMC(vars=[x1]) def run(n…

The standard way to do in PyMC3 is to create a bound distribution: In [1]: import pymc3 as pm In [2]: BoundNormal=pm.Bound(pm.Normal, 0, 1) In [3]: with pm.Model(): ...: bound_mu = BoundNormal('mu', mu=0., sd=1.) ...: trace = pm.sample() Notice that, you cannot assign observation …

The Normal distribution with upper and lower bound

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dreamqin68 December 14, 2017, 1:16pm 3

Thanks very much !

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The Normal distribution with upper and lower bound

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