Use exportS3Method NULL for S3 methods

Author: yoshidk6

R/jm_make_assoc_terms.R

@@ -392,7 +392,7 @@ get_element <- function(parts, m = 1, which = "eta", ...) {
 collapse_within_groups <- function(eta, grp_idx, grp_assoc = "sum") {
   UseMethod("collapse_within_groups")
 }
-#' @noRd
+#' @exportS3Method NULL
 collapse_within_groups.default <- function(eta, grp_idx, grp_assoc) {
   N <- nrow(grp_idx)
   val <- rep(NA, N)
@@ -402,7 +402,7 @@ collapse_within_groups.default <- function(eta, grp_idx, grp_assoc) {
   }
   val
 }
-#' @noRd
+#' @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/log_lik.R

@@ -202,7 +202,7 @@ ll_fun <- function(x, m = NULL) {
 #   N = number of observations
 #' @noRd
 ll_args <- function(object, ...) UseMethod("ll_args")
-#' @noRd
+#' @exportS3Method NULL
 ll_args.stanreg <- function(object, newdata = NULL, offset = NULL, m = NULL, 
                             reloo_or_kfold = FALSE, ...) {
   validate_stanreg_object(object)
@@ -513,7 +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
-#' @noRd
+#' @exportS3Method NULL
 ll_args.stanjm <- function(object, data, pars, m = 1, 
                            reloo_or_kfold = FALSE, ...) {
   validate_stanjm_object(object)
@@ -871,7 +871,7 @@ evaluate_log_survival <- function(log_haz, qnodes, qwts) {
   UseMethod("evaluate_log_survival")
 }
 
-#' @noRd
+#' @exportS3Method NULL
 evaluate_log_survival.default <- function(log_haz, qnodes, qwts) {
   # convert log hazard to hazard
   haz <- exp(log_haz)
@@ -884,7 +884,7 @@ evaluate_log_survival.default <- function(log_haz, qnodes, qwts) {
   -cum_haz
 }
 
-#' @noRd
+#' @exportS3Method NULL
 evaluate_log_survival.matrix <- function(log_haz, qnodes, qwts) {
   # convert log hazard to hazard
   haz <- exp(log_haz)

R/loo-prediction.R

@@ -155,7 +155,7 @@ loo_predictive_interval.stanreg <-
 
 # internal ----------------------------------------------------------------
 
-#' @noRd
+#' @exportS3Method NULL
 psis.stanreg <- function(log_ratios, ...) {
   object <- log_ratios
   message("Running PSIS to compute weights...")

R/misc.R

@@ -549,15 +549,15 @@ set_prior_scale <- function(scale, default, link) {
 linear_predictor <- function(beta, x, offset = NULL) {
   UseMethod("linear_predictor")
 }
-#' @noRd
+#' @exportS3Method NULL
 linear_predictor.default <- function(beta, x, offset = NULL) {
   eta <- as.vector(if (NCOL(x) == 1L) x * beta else x %*% beta)
   if (length(offset))
     eta <- eta + offset
 
   return(eta)
 }
-#' @noRd
+#' @exportS3Method NULL
 linear_predictor.matrix <- function(beta, x, offset = NULL) {
   if (NCOL(beta) == 1L) 
     beta <- as.matrix(beta)
@@ -633,24 +633,24 @@ get_z.stanmvreg <- function(object, m = NULL, ...) {
 # @param x A stanreg object, family object, or string. 
 # @param ... Other arguments passed to methods. For a \code{stanmvreg} object
 #   this can be an integer \code{m} specifying the submodel.
-# @return The inverse link function associated with x.
+# @return The inverse link function associated with x
 #' @noRd
 linkinv <- function(x, ...) UseMethod("linkinv")
-#' @noRd
+#' @exportS3Method NULL
 linkinv.stanreg <- function(x, ...) {
   if (is(x, "polr")) polr_linkinv(x) else family(x)$linkinv
 }
-#' @noRd
+#' @exportS3Method NULL
 linkinv.stanmvreg <- function(x, m = NULL, ...) {
   ret <- lapply(family(x), `[[`, "linkinv")
   stub <- get_stub(x)
   if (!is.null(m)) ret[[m]] else list_nms(ret, stub = stub)
 }
-#' @noRd
+#' @exportS3Method NULL
 linkinv.family <- function(x, ...) {
   x$linkinv
 }
-#' @noRd
+#' @exportS3Method NULL
 linkinv.character <- function(x, ...) {
   stopifnot(length(x) == 1)
   polr_linkinv(x)

R/predictive_error.R

@@ -141,7 +141,7 @@ predictive_error.ppd <- function(object, y, ...) {
 #   is available. The argument \code{u} specifies the time at which the 
 #   prediction error should be calculated (i.e. the time horizon).
 #   
-#' @noRd
+#' @exportS3Method NULL
 predictive_error.stanmvreg <-
   function(object,
            newdataLong = NULL,

R/stan_glm.fit.R

@@ -902,16 +902,18 @@ pad_reTrms <- function(Ztlist, cnms, flist) {
 #   stats)
 # @param columns Do the columns (TRUE) or rows (FALSE) correspond to the 
 #   variables?
-unpad_reTrms <- function(x, ...) UseMethod("unpad_reTrms")
+
 #' @noRd
+unpad_reTrms <- function(x, ...) UseMethod("unpad_reTrms")
+#' @exportS3Method NULL
 unpad_reTrms.default <- function(x, ...) {
   if (is.matrix(x) || is.array(x))
     return(unpad_reTrms.array(x, ...))
   keep <- !grepl("_NEW_", names(x), fixed = TRUE)
   x[keep]
 }
 
-#' @noRd
+#' @exportS3Method NULL
 unpad_reTrms.array <- function(x, columns = TRUE, ...) {
   ndim <- length(dim(x))
   if (ndim > 3)
@@ -945,7 +947,7 @@ make_b_nms <- function(group, m = NULL, stub = "Long") {
                                    levels(group$flist[[nm]])))))
     }
   }
-  return(b_nms)  
+  return(b_nms)
 }
 
 

R/stanreg_list.R

@@ -281,7 +281,7 @@ stanreg_list_families <- function(mods) {
 rename_loos <- function(x,...) UseMethod("rename_loos")
 
 # Change model_name attributes of a loo/waic/kfold object stored in a stanreg object,
-#' @noRd
+#' @exportS3Method NULL
 rename_loos.stanreg <- function(x, new_model_name,...) {
   for (criterion in c("loo", "waic", "kfold")) {
      if (!is.null(x[[criterion]])) {
@@ -293,7 +293,7 @@ rename_loos.stanreg <- function(x, new_model_name,...) {
 
 # Change model_name attributes of loo/waic/kfold objects to correspond to 
 # model names used for stanreg_list
-#' @noRd
+#' @exportS3Method NULL
 rename_loos.stanreg_list <- function(x, ...) {
   for (j in seq_along(x)) {
     x[[j]] <- rename_loos.stanreg(x[[j]], new_model_name = names(x)[j])