prior_spike_slab: Specify a spike-and-slab prior for variable selection

In smoothbp: Hierarchical Piecewise Regression with Smoothed Change-Points

Specify a spike-and-slab prior for variable selection

Description

Used with smoothbp_ss() to place a point-mass spike at zero on selected coefficients.

Usage

prior_spike_slab(
  pi = 0.5,
  slab = prior_normal(0, 2),
  learn_pi = FALSE,
  a = 1,
  b = 1
)

Arguments

pi	Prior inclusion probability. Default 0.5.
slab	A prior_normal() object for the slab component.
learn_pi	Logical; if TRUE, place a Beta(a, b) hyperprior on pi.
a	Shape parameter for the Beta hyperprior. Default 1.
b	Shape parameter for the Beta hyperprior. Default 1.

Value

A smoothbp_spike_slab object.

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