doc+fix: cmd check warnings

Author: dshemetov

R/layer_yeo_johnson.R

@@ -4,10 +4,10 @@
 #'
 #' @param frosting a `frosting` postprocessor. The layer will be added to the
 #'   sequence of operations for this frosting.
+#' @param lambdas Internal. A data frame of lambda values to be used for
+#'   inverting the transformation.
 #' @param ... One or more selector functions to scale variables
 #'   for this step. See [recipes::selections()] for more details.
-#' @param df a data frame that contains the population data to be used for
-#'   inverting the existing scaling.
 #' @param by A (possibly named) character vector of variables to join by.
 #' @param id a random id string
 #'
@@ -56,7 +56,7 @@ layer_epi_YeoJohnson <- function(frosting, ..., lambdas = NULL, by = NULL, id =
 }
 
 layer_epi_YeoJohnson_new <- function(lambdas, by, terms, id) {
-  epipredict:::layer("epi_YeoJohnson", lambdas = lambdas, by = by, terms = terms, id = id)
+  layer("epi_YeoJohnson", lambdas = lambdas, by = by, terms = terms, id = id)
 }
 
 #' @export
@@ -94,7 +94,7 @@ slather.layer_epi_YeoJohnson <- function(object, components, workflow, new_data,
   # Establish the join columns.
   object$by <- object$by %||%
     intersect(
-      epipredict:::epi_keys_only(components$predictions),
+      epi_keys_only(components$predictions),
       colnames(select(lambdas, -starts_with(".lambda_")))
     )
   joinby <- list(x = names(object$by) %||% object$by, y = object$by)
@@ -180,7 +180,7 @@ slather.layer_epi_YeoJohnson <- function(object, components, workflow, new_data,
 #' @export
 print.layer_epi_YeoJohnson <- function(x, width = max(20, options()$width - 30), ...) {
   title <- "Yeo-Johnson transformation (see `lambdas` object for values) on "
-  epipredict:::print_layer(x$terms, title = title, width = width)
+  print_layer(x$terms, title = title, width = width)
 }
 
 # Inverse Yeo-Johnson transformation

R/step_yeo_johnson.R

@@ -4,6 +4,14 @@
 #' transform data using a Yeo-Johnson transformation. This fork works with panel
 #' data and is meant for epidata.
 #'
+#' @param recipe A recipe object. The step will be added to the
+#'  sequence of operations for this recipe.
+#' @param ... One or more selector functions to choose variables
+#'  for this step. See [recipes::selections()] for more details.
+#' @param role For model terms created by this step, what analysis role should
+#'  they be assigned? `lag` is default a predictor while `ahead` is an outcome.
+#' @param trained A logical for whether the selectors in `...`
+#' have been resolved by [prep()].
 #' @param lambdas Internal. A numeric vector of transformation values. This
 #'  is `NULL` until computed by [prep()].
 #' @param na_lambda_fill A numeric value to fill in for any
@@ -17,6 +25,7 @@
 #' @param skip A logical. Should the step be skipped when the recipe is
 #'  baked by [bake()]. On the `training` data, the step will always be
 #'  conducted (even if `skip = TRUE`).
+#' @param id A unique identifier for the step
 #' @template step-return
 #' @family individual transformation steps
 #' @export
@@ -219,7 +228,7 @@ bake.step_epi_YeoJohnson <- function(object, new_data, ...) {
 #' @export
 print.step_epi_YeoJohnson <- function(x, width = max(20, options()$width - 39), ...) {
   title <- "Yeo-Johnson transformation (see `lambdas` object for values) on "
-  epipredict:::print_epi_step(x$terms, x$terms, title = title, width = width)
+  print_epi_step(x$terms, x$terms, title = title, width = width)
   invisible(x)
 }
 
@@ -232,7 +241,7 @@ get_lambdas_yj_table <- function(training, col_names, limits, num_unique, na_lam
       across(all_of(col_names), ~ estimate_yj(.x, limits, num_unique, na_rm)),
       .by = all_of(epi_keys_checked)
     ) %>%
-    rename_with(~ paste0(".lambda_", .x), -all_of(epi_keys_checked))
+    dplyr::rename_with(~ paste0(".lambda_", .x), -all_of(epi_keys_checked))
 
   # Check for NAs in any of the lambda_ columns.
   # EDIT: This warning was too noisy. Keeping code around, in case we want it.