Resolve a supplied fixed-effect prior to its Gaussian (mean, sd) fields

The one place that decides whether a beta_prior argument can be expressed as a Gaussian prior on the fixed effects at all. .normalize_beta_prior() (per-coefficient) and .beta_prior_ridge_sd() (scalar ridge) both resolve through it and differ only in the shape they recycle the fields to, so a prior one accepts is a prior the other accepts.

Usage

.beta_prior_fields(beta_prior)

Arguments

beta_prior

A list (or tulpa_prior object) carrying sd and optionally mean.

Value

list(mean, sd), unrecycled.

Details

A prior with no sd is an input the fitters cannot express: substituting the default for it would replace the user's modelling statement with a different one and leave no trace on the posterior.