fix merge conflict

Author: bgoodri

.github/workflows/R-CMD-check.yaml

@@ -12,63 +12,34 @@ name: R-CMD-check
 
 jobs:
   R-CMD-check:
-    runs-on: ${{ matrix.config.os }}
+    runs-on: ${{ matrix.os }}
 
-    name: ${{ matrix.config.rstan }} RStan - ${{ matrix.config.os }} (${{ matrix.config.r }})
+    name: R CMD CHECK - ${{ matrix.os }} (${{ matrix.r }})
 
     strategy:
       fail-fast: false
       matrix:
-        config:
-          - {os: macOS-latest, r: 'devel', rstan: 'CRAN'}
-          - {os: macOS-latest, r: 'release', rstan: 'CRAN'}
-          - {os: windows-latest, r: 'devel', rstan: 'CRAN'}
-          - {os: windows-latest, r: 'release', rstan: 'CRAN'}
-          - {os: ubuntu-latest, r: 'devel', rstan: 'CRAN'}
-          - {os: ubuntu-latest, r: 'release', rstan: 'CRAN'}
-          - {os: ubuntu-latest, r: 'oldrel', rstan: 'CRAN'}
-
-          - {os: macOS-latest, r: 'release', rstan: 'Preview'}
-          - {os: windows-latest, r: 'release', rstan: 'Preview'}
+        os: [macOS-latest, windows-latest, ubuntu-latest, ubuntu-24.04-arm]
+        r: ['devel', 'release', 'oldrel']
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
-      RSPM: ${{ matrix.config.rspm }}
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      TESTTHAT_CPUS: 4
 
     steps:
-      - uses: n1hility/cancel-previous-runs@v2
+      - uses: n1hility/cancel-previous-runs@master
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
-          workflow: R-CMD-check.yaml
         if: "!startsWith(github.ref, 'refs/tags/') && github.ref != 'refs/heads/master'"
 
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@main
 
-      - uses: r-lib/actions/setup-r@v2
+      - uses: r-lib/actions/setup-r@v2-branch
         with:
-          r-version: ${{ matrix.config.r }}
+          r-version: ${{ matrix.r }}
 
-      - uses: r-lib/actions/setup-pandoc@v2
-      - uses: r-lib/actions/setup-r-dependencies@v2
+      - uses: r-lib/actions/setup-pandoc@v2-branch
+      - uses: r-lib/actions/setup-r-dependencies@v2-branch
         with:
-          cache-version: 2
           extra-packages: any::rcmdcheck any::betareg any::HSAUR3 any::biglm any::gamm4 any::V8
-
-      - name: Install RStan Preview if Needed
-        run: |
-          if ("${{ matrix.config.rstan }}" == "Preview") {
-            install.packages("rstan", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
-          }
-        shell: Rscript {0}
-
-      - uses: r-lib/actions/check-r-package@v2
-        with:
-          args: 'c("--no-manual", "--as-cran", "--ignore-vignettes")'
-          build_args: '"--no-build-vignettes"'
-
-      - name: Upload check results
-        if: failure()
-        uses: actions/upload-artifact@main
-        with:
-          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
-          path: check
+      - uses: r-lib/actions/check-r-package@v2-branch

.gitignore

@@ -8,11 +8,15 @@ src/stan_files/*.hpp
 src/rstanarm.so
 src/rstanarm.dll
 src/init.o
-man/*.Rd
 !man/rstanarm-internal.Rd
 vignettes/*.R
 !vignettes/*.Rmd
 vignettes/*.html
 vignettes/*_files
 .DS_Store
 revdep/*
+*.o
+*.cc
+*.h
+src/Makevars
+R/stanmodels.R

DESCRIPTION

@@ -48,7 +48,8 @@ Imports:
     stats,
     survival (>= 2.40.1),
     RcppParallel (>= 5.0.1),
-    utils
+    utils,
+    reformulas
 Suggests:
     biglm,
     betareg,
@@ -75,4 +76,4 @@ UseLTO: true
 NeedsCompilation: yes
 URL: https://mc-stan.org/rstanarm/, https://discourse.mc-stan.org
 BugReports: https://github.com/stan-dev/rstanarm/issues
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2

NAMESPACE

@@ -229,7 +229,6 @@ importFrom(ggplot2,scale_x_discrete)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,theme_bw)
 importFrom(ggplot2,xlab)
-importFrom(lme4,findbars)
 importFrom(lme4,fixef)
 importFrom(lme4,glFormula)
 importFrom(lme4,glmer)
@@ -262,6 +261,7 @@ importFrom(posterior,as_draws_df)
 importFrom(posterior,as_draws_list)
 importFrom(posterior,as_draws_matrix)
 importFrom(posterior,as_draws_rvars)
+importFrom(reformulas,findbars)
 importFrom(rstan,constrain_pars)
 importFrom(rstan,extract)
 importFrom(rstan,extract_sparse_parts)

R/doc-rstanarm-package.R

@@ -17,9 +17,6 @@
 
 #' Applied Regression Modeling via RStan
 #'
-#' @docType package
-#' @name rstanarm-package
-#' @aliases rstanarm
 #' @useDynLib rstanarm, .registration = TRUE
 #'
 #' @import methods
@@ -104,4 +101,4 @@
 #' @template reference-bayesvis
 #' @template reference-muth
 #'
-NULL
+"_PACKAGE"

R/jm_data_block.R

@@ -148,13 +148,13 @@ reformulate_lhs <- function(x) {
 # Reformulate an expression as the RHS of a model formula
 # 
 # @param x The expression to reformulate
-# @param subbars A logical specifying whether to call lme4::subbars
+# @param subbars A logical specifying whether to call reformulas::subbars
 #   on the result
 # @return A model formula
 reformulate_rhs <- function(x, subbars = FALSE) {
   fm <- formula(substitute(~ RHS, list(RHS = x)))
   if (subbars) {
-    lme4::subbars(fm)
+    reformulas::subbars(fm)
   } else {
     fm
   }
@@ -579,7 +579,7 @@ rename_t_and_cauchy <- function(prior_stuff, has) {
 #   has_aux: logical specifying whether the glmer submodel 
 #     requires an auxiliary parameter.
 handle_y_mod <- function(formula, data, family) {
-  mf <- stats::model.frame(lme4::subbars(formula), data)
+  mf <- stats::model.frame(reformulas::subbars(formula), data)
   if (!length(formula) == 3L)
     stop2("An outcome variable must be specified.")
 
@@ -647,7 +647,7 @@ make_y_for_stan <- function(formula, model_frame, family) {
 #   N,K: number of rows (observations) and columns (predictors) in the
 #     fixed effects model matrix
 make_x_for_stan <- function(formula, model_frame) {
-  x_form <- lme4::nobars(formula)
+  x_form <- reformulas::nobars(formula)
   x <- model.matrix(x_form, model_frame)
   has_intercept <- check_for_intercept(x, logical = TRUE)
   xtemp <- drop_intercept(x)
@@ -680,7 +680,7 @@ make_x_for_stan <- function(formula, model_frame) {
 #     grouping factor
 #   ngrps: a vector with the number of groups for each grouping factor 
 make_z_for_stan <- function(formula, model_frame) {
-  bars <- lme4::findbars(formula)
+  bars <- reformulas::findbars(formula)
   if (length(bars) > 2L)
     stop2("A maximum of 2 grouping factors are allowed.")
   z_parts <- lapply(bars, split_at_bars)
@@ -816,7 +816,7 @@ append_mvmer_famlink <- function(family, is_bernoulli = FALSE) {
 #   - the formula part (ie. the formula on the LHS of "|"), and 
 #   - the name of the grouping factor (ie. the variable on the RHS of "|")
 #
-# @param x Random effects part of a model formula, as returned by lme4::findbars
+# @param x Random effects part of a model formula, as returned by reformulas::findbars
 # @return A named list with the following elements:
 #   re_form: a formula specifying the random effects structure
 #   group_var: the name of the grouping factor
@@ -919,13 +919,13 @@ check_id_list <- function(id_var, y_flist) {
 #
 # @param terms The existing model frame terms object
 # @param formula The formula that was used to build the model frame
-#   (but prior to having called lme4::subbars on it!)
+#   (but prior to having called reformulas::subbars on it!)
 # @param data The data frame that was used to build the model frame
 # @return A terms object with predvars.fixed and predvars.random as
 #   additional attributes
 append_predvars_attribute <- function(terms, formula, data) {
-  fe_form <- lme4::nobars(formula)
-  re_form <- lme4::subbars(justRE(formula, response = TRUE))
+  fe_form <- reformulas::nobars(formula)
+  re_form <- reformulas::subbars(justRE(formula, response = TRUE))
   fe_frame <- stats::model.frame(fe_form, data)
   re_frame <- stats::model.frame(re_form, data)
   fe_terms <- attr(fe_frame, "terms")
@@ -1587,7 +1587,7 @@ parse_assoc_data <- function(x, user_x) {
     if (identical(length(fm), 3L))
       stop(paste0("Formula specified for '", x, "' association structure should not ",
                   "include a response."), call. = FALSE)
-    if (length(lme4::findbars(fm)))
+    if (length(reformulas::findbars(fm)))
       stop(paste0("Formula specified for '", x, "' association structure should only ",
                   "include fixed effects."), call. = FALSE)
     if (fm[[2L]] == 1)

R/jm_make_assoc_parts.R

@@ -190,17 +190,17 @@ make_assoc_parts_for_stan <- function(newdata, y_mod, include_Zt = TRUE) {
   # construct model frame using predvars
   formula <- use_predvars(y_mod, keep_response = FALSE)
   data <- as.data.frame(newdata)
-  model_frame <- stats::model.frame(lme4::subbars(formula), data)
+  model_frame <- stats::model.frame(reformulas::subbars(formula), data)
 
   # fe design matrices
-  x_form <- lme4::nobars(formula)
+  x_form <- reformulas::nobars(formula)
   x <- model.matrix(x_form, model_frame)
   xtemp <- drop_intercept(x)
   x_bar <- y_mod$x$x_bar
   xtemp <- sweep(xtemp, 2, x_bar, FUN = "-")
 
   # re design matrices
-  bars <- lme4::findbars(formula)
+  bars <- reformulas::findbars(formula)
   if (length(bars) > 2L)
     stop2("A maximum of 2 grouping factors are allowed.")
   z_parts <- lapply(bars, split_at_bars)
@@ -214,7 +214,7 @@ make_assoc_parts_for_stan <- function(newdata, y_mod, include_Zt = TRUE) {
 
   # optionally add the sparse Zt matrix
   if (include_Zt) 
-    ret$Zt <- lme4::mkReTrms(bars, model_frame)$Zt
+    ret$Zt <- reformulas::mkReTrms(bars, model_frame)$Zt
 
   # add offset values
   if ('offset' %in% colnames(newdata))

R/jm_make_assoc_terms.R

@@ -388,9 +388,11 @@ get_element <- function(parts, m = 1, which = "eta", ...) {
 # @param grp_assoc Character string, the function to use to collapse
 #   across the lower level units clustered within individuals.
 # @return A vector or matrix, depending on the method called.
+#' @noRd
 collapse_within_groups <- function(eta, grp_idx, grp_assoc = "sum") {
   UseMethod("collapse_within_groups")
 }
+#' @exportS3Method NULL
 collapse_within_groups.default <- function(eta, grp_idx, grp_assoc) {
   N <- nrow(grp_idx)
   val <- rep(NA, N)
@@ -400,6 +402,7 @@ collapse_within_groups.default <- function(eta, grp_idx, grp_assoc) {
   }
   val
 }
+#' @exportS3Method NULL
 collapse_within_groups.matrix <- function(eta, grp_idx, grp_assoc) {
   N <- nrow(grp_idx)
   val <- matrix(NA, nrow = nrow(eta), ncol = N)

R/launch_shinystan.R

@@ -43,7 +43,7 @@
 #'   used with ShinyStan. The only exception is that ShinyStan does not 
 #'   currently support \pkg{rstanarm} models fit using 
 #'   \code{algorithm='optimizing'}. See the 
-#'   \pkg{\link[=shinystan-package]{shinystan}} package documentation for more 
+#'   \pkg{\link[shinystan:shinystan-package]{shinystan}} package documentation for more 
 #'   information.
 #'   
 #' @section Faster launch times:

R/log_lik.R

@@ -200,7 +200,9 @@ ll_fun <- function(x, m = NULL) {
 #   just a single MCMC draw).
 # @return a named list with elements data, draws, S (posterior sample size) and
 #   N = number of observations
+#' @noRd
 ll_args <- function(object, ...) UseMethod("ll_args")
+#' @exportS3Method NULL
 ll_args.stanreg <- function(object, newdata = NULL, offset = NULL, m = NULL, 
                             reloo_or_kfold = FALSE, ...) {
   validate_stanreg_object(object)
@@ -511,6 +513,7 @@ ll_args.stanreg <- function(object, newdata = NULL, offset = NULL, m = NULL,
 # @param pars Output from extract_pars
 # @param m Integer specifying which submodel
 # @param reloo_or_kfold logical. TRUE if ll_args is for reloo or kfold
+#' @exportS3Method NULL
 ll_args.stanjm <- function(object, data, pars, m = 1, 
                            reloo_or_kfold = FALSE, ...) {
   validate_stanjm_object(object)
@@ -863,10 +866,12 @@ evaluate_log_basehaz <- function(times, basehaz, coefs) {
 #   at which the log hazard was evaluated for each individual.
 # @param qwts A vector of unstandardised GK quadrature weights.
 # @return A vector or matrix of log survival probabilities.
+#' @noRd
 evaluate_log_survival <- function(log_haz, qnodes, qwts) {
   UseMethod("evaluate_log_survival")
 }
 
+#' @exportS3Method NULL
 evaluate_log_survival.default <- function(log_haz, qnodes, qwts) {
   # convert log hazard to hazard
   haz <- exp(log_haz)
@@ -879,6 +884,7 @@ evaluate_log_survival.default <- function(log_haz, qnodes, qwts) {
   -cum_haz
 }
 
+#' @exportS3Method NULL
 evaluate_log_survival.matrix <- function(log_haz, qnodes, qwts) {
   # convert log hazard to hazard
   haz <- exp(log_haz)