Replace tidybayes dependency with ggdist and rstantools

tidybayes depends on arrayhelpers which is scheduled for CRAN archival.
Replace tidybayes::add_*_draws() with direct posterior_epred/linpred/predict
via rstantools generics + a new .pp_matrix_to_draws_tbl() reshape helper.
Replace tidybayes::median_qi() with ggdist::median_qi().

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: yoshidk6

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: BayesERtools
 Type: Package
 Title: Bayesian Exposure-Response Analysis Tools
-Version: 0.2.5
+Version: 0.2.5.9000
 Authors@R: 
     c(person("Kenta", "Yoshida", , "yoshida.kenta.6@gmail.com", role = c("aut", "cre"),
              comment = c(ORCID = "0000-0003-4967-3831")),
@@ -27,7 +27,7 @@ Depends:
 URL: https://genentech.github.io/BayesERtools/, https://genentech.github.io/BayesERbook/
 Config/testthat/edition: 3
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Imports: 
     dplyr,
     tidyr,
@@ -38,8 +38,9 @@ Imports:
     rlang,
     rstanarm,
     rstanemax (>= 0.1.9),
+    rstantools,
     loo,
-    tidybayes,
+    ggdist,
     posterior
 Suggests: 
     testthat (>= 3.0.0),

NEWS.md

@@ -1,3 +1,13 @@
+# BayesERtools 0.2.5.9000
+
+## Major changes
+
+* Replaced `tidybayes` dependency with `ggdist` and `rstantools` to avoid
+  CRAN archival risk from `tidybayes`'s dependency on `arrayhelpers`.
+  `tidybayes::add_*_draws()` calls replaced with direct `posterior_epred()` /
+  `posterior_linpred()` / `posterior_predict()` via `rstantools` generics.
+  `tidybayes::median_qi()` replaced with `ggdist::median_qi()`.
+
 # BayesERtools 0.2.5
 
 ## Major changes

R/coveff.R

@@ -65,7 +65,10 @@ sim_coveff <- function(
   df_for_sim <- spec_coveff_to_df_sim(spec_coveff)
 
   linpred_draws <-
-    tidybayes::add_linpred_draws(df_for_sim, extract_mod(ermod))
+    .pp_matrix_to_draws_tbl(
+      rstantools::posterior_linpred(extract_mod(ermod), newdata = df_for_sim),
+      df_for_sim, ".linpred"
+    )
 
   linpred_draws_ref <-
     linpred_draws |>
@@ -102,7 +105,11 @@ sim_coveff <- function(
 
   linpred_med_qi <-
     linpred_draws_3 |>
-    tidybayes::median_qi(.width = qi_width) |>
+    dplyr::group_by(dplyr::across(
+      !dplyr::any_of(c(".chain", ".iteration", ".draw",
+        ".odds_ratio", ".response_diff"))
+    )) |>
+    ggdist::median_qi(.width = qi_width) |>
     dplyr::arrange(var_order, value_order)
 
   # Determine which columns to select based on model type

R/ersim-methods.R

@@ -72,15 +72,17 @@ extract_var_cov.ersim_med_qi <- function(x) attr(x, "var_cov")
 #'
 calc_ersim_med_qi <- function(x, qi_width = 0.95) {
   var_exposure_sym <- rlang::sym(extract_var_exposure(x))
-  x_grouped <- x
-
   if (inherits(x, "ersim_marg")) {
     x_grouped <- dplyr::group_by(x, .id_exposure, !!var_exposure_sym)
+  } else {
+    x_grouped <- dplyr::group_by(x, dplyr::across(
+      !c(.chain, .iteration, .draw, .epred, .linpred, .prediction)
+    ))
   }
 
   simdata_med_qi <-
     x_grouped |>
-    tidybayes::median_qi(.width = qi_width) |>
+    ggdist::median_qi(.width = qi_width) |>
     dplyr::as_tibble()
 
   # Create dummy ermod to feed to ersim class constructor

R/sim_ermod.R

@@ -25,7 +25,7 @@
 #' `.epred` is on the probability scale. `.prediction` is the predicted
 #' response with residual variability (or in case of binary endpoint,
 #' the predicted yes (1) or no (0) for event occurrence).
-#' See [tidybayes::add_epred_draws()] for more details.
+#' See [rstantools::posterior_epred()] for more details.
 #'
 #' In case of `output_type = "median_qi"`, it returns `ersim_med_qi` object.
 #'
@@ -87,23 +87,27 @@ sim_er <- function(
   n_draws_sim <- chech_ndraws(mod, n_draws_sim)
 
   simdata_epred <-
-    tidybayes::add_epred_draws(newdata, mod,
-      ndraws = n_draws_sim,
-      seed = seed_sample_draws
+    .pp_matrix_to_draws_tbl(
+      .posterior_draws(rstantools::posterior_epred, mod, newdata,
+        n_draws_sim, seed_sample_draws
+      ),
+      newdata, ".epred"
     )
   simdata_linpred <-
-    tidybayes::add_linpred_draws(newdata, mod,
-      ndraws = n_draws_sim,
-      seed = seed_sample_draws
+    .pp_matrix_to_draws_tbl(
+      .posterior_draws(rstantools::posterior_linpred, mod, newdata,
+        n_draws_sim, seed_sample_draws
+      ),
+      newdata, ".linpred"
     ) |>
-    dplyr::ungroup() |>
     dplyr::select(.draw, .row, .linpred)
   simdata_predicted <-
-    tidybayes::add_predicted_draws(newdata, mod,
-      ndraws = n_draws_sim,
-      seed = seed_sample_draws
+    .pp_matrix_to_draws_tbl(
+      .posterior_draws(rstantools::posterior_predict, mod, newdata,
+        n_draws_sim, seed_sample_draws
+      ),
+      newdata, ".prediction"
     ) |>
-    dplyr::ungroup() |>
     dplyr::select(.draw, .row, .prediction)
 
   simdata <-
@@ -121,7 +125,10 @@ sim_er <- function(
 
   simdata_med_qi <-
     simdata |>
-    tidybayes::median_qi(.width = qi_width) |>
+    dplyr::group_by(dplyr::across(
+      !c(.chain, .iteration, .draw, .epred, .linpred, .prediction)
+    )) |>
+    ggdist::median_qi(.width = qi_width) |>
     dplyr::as_tibble()
 
   if (inherits(ermod, "ermod_bin")) {
@@ -406,7 +413,7 @@ sim_er_new_exp_marg <- function(
   simdata_med_qi <-
     simdata |>
     dplyr::group_by(.id_exposure, !!var_exposure_sym) |>
-    tidybayes::median_qi(.width = qi_width) |>
+    ggdist::median_qi(.width = qi_width) |>
     dplyr::as_tibble()
 
   return(new_ersim_marg_med_qi(simdata_med_qi, ermod,

R/utils-draws.R

@@ -0,0 +1,29 @@
+.posterior_draws <- function(fn, mod, newdata, n_draws, seed) {
+  set.seed(seed)
+  if (inherits(mod, c("stanemax", "stanemaxbin"))) {
+    fn(mod, newdata = newdata, ndraws = n_draws)
+  } else {
+    fn(mod, newdata = newdata, draws = n_draws)
+  }
+}
+
+.pp_matrix_to_draws_tbl <- function(mat, newdata, col_name) {
+  n_draws <- nrow(mat)
+  n_obs <- nrow(newdata)
+  draw_rows <- expand.grid(
+    .draw = seq_len(n_draws),
+    .row = seq_len(n_obs)
+  )
+  newdata |>
+    dplyr::mutate(.row = dplyr::row_number()) |>
+    dplyr::left_join(
+      dplyr::tibble(
+        .row = draw_rows$.row,
+        .chain = NA_integer_,
+        .iteration = NA_integer_,
+        .draw = draw_rows$.draw,
+        !!col_name := as.vector(mat)
+      ),
+      by = ".row"
+    )
+}

R/yyy.R

@@ -5,7 +5,7 @@ if (getRversion() >= "2.15.1") {
   # General
   utils::globalVariables(c(
     ".", "n", ":=", ".epred", ".linpred", ".prediction", ".draw", ".response",
-    ".id_exposure"
+    ".id_exposure", ".chain", ".iteration", ".row"
   ))
 
   # ggplot