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Convert shrinkr_fit to draws_df

Source: R/shrink-methods.R
as_draws_df.shrinkr_fit.Rd

Extracts posterior draws in tidy format using the posterior package. By default returns user-facing parameters (mu, tau, theta, etc.) and excludes internal parameterization details. Set include_internals = TRUE to access all parameters including theta_c and z.

Usage

# S3 method for class 'shrinkr_fit'
as_draws_df(x, variables = NULL, include_internals = FALSE, ...)

Arguments

x

A shrinkr_fit object from shrink().

variables

Character vector of parameter names to extract. Options include:

  • "mu" - Global mean

  • "tau" - Heterogeneity SD

  • "tau_squared" - Heterogeneity variance

  • "theta" or "theta[i]" - Subgroup effects

If NULL (default), returns all user-facing parameters.

include_internals

Logical; if TRUE, includes internal Stan parameters (theta_c, z) used for parameterization. Default FALSE. Only applies when variables = NULL.

...

Additional arguments passed to posterior::as_draws_df().

Value

A posterior::draws_df with columns for chain, iteration, draw, and requested parameters.

See also

shrink() for fitting models, extract_mu_tau() for hyperparameters only

Examples

set.seed(1)
draws <- data.frame(
  mu = rnorm(20, 0.2, 0.05),
  tau = abs(rnorm(20, 0.3, 0.03)),
  `theta[1]` = rnorm(20, 0.0, 0.1),
  `theta[2]` = rnorm(20, 0.3, 0.1),
  `theta[3]` = rnorm(20, 0.5, 0.1),
  check.names = FALSE
)
draws$tau_squared <- draws$tau^2
fit <- list(
  fit = posterior::as_draws_df(draws),
  data = list(
    G = 3, K = 1, centered = FALSE,
    vars = c("group1", "group2", "group3"),
    quantiles = data.frame(
      q2.5 = c(-0.20, 0.10, 0.30),
      q50 = c(0.00, 0.30, 0.50),
      q97.5 = c(0.20, 0.50, 0.70)
    )
  ),
  summary = posterior::summarise_draws(
    posterior::as_draws_df(draws),
    "mean", "sd",
    ~posterior::quantile2(., probs = c(0.025, 0.5, 0.975))
  ),
  diagnostics = list(n_divergent = 0, max_treedepth = 0, n_leapfrog = 0)
)
class(fit) <- "shrinkr_fit"
all_draws <- posterior::as_draws_df(fit)
posterior::variables(all_draws)
#> [1] "mu"          "tau"         "theta[1]"    "theta[2]"    "theta[3]"   
#> [6] "tau_squared"
theta_draws <- posterior::as_draws_df(fit, variables = c("theta[1]", "theta[2]"))