stan-dev · aloctavodia · May 16, 2026 · May 6, 2026 · May 14, 2026 · May 14, 2026
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -90,5 +90,5 @@ Additional_repositories:
     https://stan-dev.r-universe.dev/
 LazyData: TRUE
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.3
 VignetteBuilder: knitr, rmarkdown
+Config/roxygen2/version: 8.0.0
diff --git a/R/methods.R b/R/methods.R
@@ -19,7 +19,7 @@
 #' the draws, while the aleatoric uncertainty from the data model is
 #' not included. However, the estimated means of both methods averaged
 #' across draws should be very similar.
-#' 
+#'
 #' The [proj_linpred()] function draws from the projected posterior of the
 #' linear predictors, that is, draws before applying any link functions
 #' or other transformations. These linear predictors can also be
@@ -639,6 +639,11 @@ proj_predict_aux <- function(proj, newdata, offsetnew, weightsnew,
   return(structure(pppd_out, cats = cats_aug))
 }
 
+# Needed to avoid a NOTE in `R CMD check`:
+if (getRversion() >= package_version("2.15.1")) {
+  utils::globalVariables("fontsize")
+}
+
 #' Plot predictive performance
 #'
 #' This is the [plot()] method for `vsel` objects (returned by [varsel()] or
@@ -1158,9 +1163,9 @@ plot.vsel <- function(
       x_color_txt <- "black"
     }
     pp <- pp +
-      if (packageVersion("ggplot2") < "4.0.0") {
+      if (utils::packageVersion("ggplot2") < "4.0.0") {
         geom_text(aes(y = -Inf, label = .data[["size_chr"]]), vjust = -0.5,
-                        color = x_color_txt)
+                  color = x_color_txt)
       } else {
         geom_text(aes(y = -Inf, label = .data[["size_chr"]],
                       size = from_theme(fontsize * 0.7)),

diff --git a/man/as.matrix.projection.Rd b/man/as.matrix.projection.Rd
diff --git a/man/as_draws_matrix.projection.Rd b/man/as_draws_matrix.projection.Rd
diff --git a/man/cl_agg.Rd b/man/cl_agg.Rd
diff --git a/man/cv_varsel.Rd b/man/cv_varsel.Rd
diff --git a/man/df_binom.Rd b/man/df_binom.Rd
diff --git a/man/df_gaussian.Rd b/man/df_gaussian.Rd
diff --git a/man/extend_family.Rd b/man/extend_family.Rd
diff --git a/man/mesquite.Rd b/man/mesquite.Rd
diff --git a/man/plot.cv_proportions.Rd b/man/plot.cv_proportions.Rd
diff --git a/man/plot.vsel.Rd b/man/plot.vsel.Rd
diff --git a/man/pred-projection.Rd b/man/pred-projection.Rd
diff --git a/man/predict.refmodel.Rd b/man/predict.refmodel.Rd
diff --git a/man/project.Rd b/man/project.Rd
diff --git a/man/projpred-package.Rd b/man/projpred-package.Rd
diff --git a/man/refmodel-init-get.Rd b/man/refmodel-init-get.Rd
diff --git a/man/varsel.Rd b/man/varsel.Rd
diff --git a/tests/testthat/test_datafit.R b/tests/testthat/test_datafit.R
@@ -695,10 +695,17 @@ test_that(paste(
                           nterms = 0:nterms, refit_prj = FALSE)
 
     # compute the results for the Lasso
-    lasso <- glmnet::glmnet(x, y_glmnet,
-                            family = fam$family, weights = weights,
-                            lambda.min.ratio = lambda_min_ratio,
-                            nlambda = nlambda, thresh = 1e-12)
+    if (packageVersion("glmnet") < "5.0") {
+      lasso <- glmnet::glmnet(x, y_glmnet,
+                              family = fam$family, weights = weights,
+                              lambda.min.ratio = lambda_min_ratio,
+                              nlambda = nlambda, thresh = 1e-12)
+    } else {
+      lasso <- glmnet::glmnet(x, y_glmnet,
+                              family = fam$family, weights = weights,
+                              lambda.min.ratio = lambda_min_ratio,
+                              nlambda = nlambda, control = list(thresh = 1e-12))
+    }
     predictor_ranking <- predict(lasso, type = "nonzero", s = lasso$lambda)
     nselected <- sapply(predictor_ranking, function(e) length(e))
     lambdainds <- sapply(unique(nselected), function(nterms) {