Hi! I’m currently implementing a Stan model using the Pystan interface and I have one of my parameters with a prior distribution \text{Beta}(\alpha_0,\beta_0 ). The parameter in question is usually calibrated with data such that the beta distribution has a specific mean and variance (currently,…

The mean and variance of a beta density are not independent – if \mu is the mean then the variance is bounded above by \mu \cdot (1 - \mu). In regression settings where one wants to model the location of the beta density the breadth of the density is controlled not by the variance but rather by a c…

Convention for user-calibrated priors

Modeling

patohdzs April 7, 2021, 4:14pm 3

Thank you!

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Convention for user-calibrated priors

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