the model is like this:

with pm.Model() as model_t:

mu = pm.Uniform(‘mu’, 0, 1)

sigma = pm.HalfNormal(‘sigma’, sd = 10)

nu = pm.Exponential(‘nu’, 1/30)

y = pm.StudentT(‘y’, mu=mu, sd=sigma, nu=nu, observed=data)

trace_t = pm.sample(1100)

chain_t = trace_t[100:]

Now I know the prior mu-3*sigma should less than 0.001, how should I put this knowledge in to this model?

Thanks!