Extract posterior coefficient summaries

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)
#>      mu[x] Omega[x,x] 
#>  1.1179023  0.4330456 
head(coef(model, level = "individual"))
#>          x
#> 1 1.225240
#> 2 1.093412
#> 3 1.234794
#> 4 1.152078
#> 5 1.205390
#> 6 1.255007