smoothbp_priors: Collect priors for all model parameters

In smoothbp: Hierarchical Piecewise Regression with Smoothed Change-Points

Collect priors for all model parameters

Description

Each argument accepts either:

• A single prior_normal() applied to all coefficients of that parameter, or

• A named list mapping coefficient names (matching column names of the design matrix) to individual prior_normal() objects.

Usage

smoothbp_priors(
  b0 = prior_normal(0, 10),
  b1 = prior_normal(0, 2),
  deltas = prior_normal(0, 2),
  omega = prior_normal(3, 2, lb = 0),
  rho = prior_normal(3, 2, lb = 0),
  sigma = prior_invgamma(1, 1),
  sigma_u = prior_invgamma(1, 1),
  sigma_re_om = prior_invgamma(1, 1),
  sigma_re_b1 = prior_invgamma(1, 1),
  sigma_re_deltas = prior_invgamma(1, 1)
)

Arguments

b0	Prior(s) for b0 regression coefficients.
b1	Prior(s) for b1 regression coefficients.
deltas	Prior(s) for slope change coefficients (one list per segment).
omega	Prior(s) for omega coefficients (one list per segment).
rho	Prior(s) for rho coefficients (one list per segment).
sigma	prior_invgamma() for residual SD.
sigma_u	prior_invgamma() for random-effect SD.
sigma_re_om	prior_invgamma() for random-effect SD on omega.
sigma_re_b1	prior_invgamma() for random-effect SD on b1.
sigma_re_deltas	prior_invgamma() for random-effect SD on deltas.

Details

For multi-breakpoint models, deltas, omega, and rho can also be lists of prior specifications (one per breakpoint slot). If a single specification is provided, it is applied to all slots.

Value

A smoothbp_priors list.

smoothbp documentation built on June 14, 2026, 9:06 a.m.