Another common way to do it is to model the largest parameter \beta_m using whatever distribution (eg normal), and then use Dirichlet distribution to get “weights”, that one adds up cumulatively to get to i-th effect. It has a disadvantage that it doesn’t allow some parameters to be positive and some negative, though. brms does that in R world: Estimating Monotonic Effects with brms
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