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*sigm…

If you want a hard constraint then you can use Potential like @sammosummo suggested example code: 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=d…

How to put prior knowledge in to student-t model

Questions

huwendi2006 May 19, 2020, 2:15am 3

Hi sammosummo:
I’m sorry I didn’t get your word, could you be more specific? thanks

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How to put prior knowledge in to student-t model

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