Hi, a very simple inference question for you: I have a prior with a mean and std, and some of evidence data. Is it the correct way to include both mean and std in one distribution like so: prior = pm.Normal(“prior”,mu=mean, sd=std) pm.Normal(“likelihood”, mu=prior, observed=data) or should one …

In the first case, you’re providing a prior distribution with fixed parameters, whereas in the latter you’re providing distributions over the parameters as well, which means they can be learned and changed; though I believe the latter case should be with pm.Model() as model: sd = pm.Normal(“sd”…

Basic bayesian inference formulation

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BjornHartmann August 19, 2020, 6:55am 6

Is there one of the two that are preferred over the other or would you say both are correct, but the latter gives the most flexibility on the posterior?

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Basic bayesian inference formulation

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