coef.RprobitB_fit: Extract posterior coefficient summaries

In RprobitB: Bayesian Probit Choice Modeling

Extract posterior coefficient summaries

Description

Returns posterior means or medians for population parameters or individual random coefficients.

Usage

## S3 method for class 'RprobitB_fit'
coef(
  object,
  type = c("mean", "median"),
  level = c("population", "individual"),
  ...
)

Arguments

object	[RprobitB_fit] Fitted choice model.
type	[character(1)] The posterior summary to return: "mean" averages the draws. "median" is more robust for skewed posteriors.
level	[character(1)] Which parameters to return: "population" returns the parameters shared by all deciders. "individual" returns the random coefficients of every decider, which requires a mixed model fitted with save_individual_draws = TRUE.
...	Currently not used.

Value

For level = "population", a named numeric vector with one value per global posterior variable that is not fixed by the normalization or the model structure. For level = "individual", a numeric matrix with deciders in rows and random effects in columns. Log-normal coefficients remain on their latent normal scale.

Examples

set.seed(1)
model <- fit(
  choice ~ x | 0,
  random_effects = "x",
  dgp_parameters = list(beta = c(x = 1), Omega = matrix(0.5)),
  chains = 1,
  save_individual_draws = TRUE
)
coef(model)
head(coef(model, level = "individual"))

RprobitB documentation built on Sept. 20, 2026, 9:07 a.m.