getting docs updated

.Rbuildignore

@@ -16,3 +16,4 @@
 ^Rmd/
 lastMiKTeXException
 ^\.zenodo\.json$
+^scratch\.R$

R/orsf.R

@@ -85,16 +85,23 @@
 #'  of randomly selected predictors, up to `n_retry` times. Default is
 #'  `n_retry = 3`. Set `n_retry = 0` to prevent any retries.
 #'
-#' @param n_thread `r roxy_n_thread_header()`
+#' @param n_thread `r roxy_n_thread_header("growing trees, computing predictions, and computing importance.")`
 #'
 #' @param mtry (_integer_) Number of predictors randomly included as candidates
 #'   for splitting a node. The default is the smallest integer greater than
 #'   the square root of the number of total predictors, i.e.,
 #'   `mtry = ceiling(sqrt(number of predictors))`
 #'
-#' @param sample_with_replacement
+#' @param sample_with_replacement (_logical_) If `TRUE` (the default),
+#'   observations are sampled with replacement when an in-bag sample
+#'   is created for a decision tree. If `FALSE`, observations are
+#'   sampled without replacement and each tree will have an in-bag sample
+#'   containing `sample_fraction`% of the original sample.
 #'
-#' @param sample_fraction
+#' @param sample_fraction (_double_) the proportion of observations that
+#'   each trees' in-bag sample will contain, relative to the number of
+#'   rows in `data`. Only used if `sample_with_replacement` is `FALSE`.
+#'   Default value is 0.632.
 #'
 #' @param leaf_min_events (_integer_) minimum number of events in a
 #'   leaf node. Default is `leaf_min_events = 1`
@@ -186,7 +193,7 @@
 #'     to the output will be the imputed version of `data`.
 #'
 #' @param verbose_progress (_logical_) if `TRUE`, progress messages are
-#'   printed in the console.
+#'   printed in the console. If `FALSE` (the default), nothing is printed.
 #'
 #' @param ... `r roxy_dots()`
 #'

R/orsf_pd.R

@@ -60,6 +60,8 @@
 #'  percentile in the object's training data. If `FALSE`, these checks are
 #'  skipped.
 #'
+#' @param n_thread `r roxy_n_thread_header("computing predictions")`
+#'
 #' @param ... `r roxy_dots()`
 #'
 #' @return a [data.table][data.table::data.table-package] containing
@@ -309,6 +311,9 @@ orsf_pred_dependence <- function(object,
 
  pred_horizon <- infer_pred_horizon(object, pred_horizon)
 
+ # make a visible binding for CRAN
+ id_variable = NULL
+
  if(is.null(prob_values)) prob_values <- c(0.025, 0.50, 0.975)
  if(is.null(prob_labels)) prob_labels <- c('lwr', 'medn', 'upr')
 

R/orsf_predict.R

@@ -45,6 +45,18 @@
 #'  observed time in `object`'s training data. If `FALSE`, these checks
 #'  are skipped.
 #'
+#' @param n_thread `r roxy_n_thread_header("computing predictions")`
+#'
+#' @param pred_aggregate (_logical_) If `TRUE` (the default), predictions
+#'   will be aggregated over all trees by taking the mean. If `FALSE`, the
+#'   returned output will contain one row per observation and one column
+#'   for each tree. If the length of `pred_horizon` is two or more and
+#'   `pred_aggregate` is `FALSE`, then the result will be a list of such
+#'   matrices, with the i'th item in the list corresponding to the i'th
+#'   value of `pred_horizon`.
+#'
+#' @inheritParams orsf
+#'
 #' @param ... `r roxy_dots()`
 #'
 #' @return a `matrix` of predictions. Column `j` of the matrix corresponds
@@ -119,15 +131,15 @@ predict.orsf_fit <- function(object,
   results <- lapply(
    X = pred_horizon,
    FUN = function(t){
-    predict(object = object,
-            new_data = new_data,
-            pred_horizon = t,
-            pred_type = pred_type,
-            na_action = na_action,
-            boundary_checks = boundary_checks,
-            n_thread = n_thread,
-            verbose_progress = verbose_progress,
-            pred_aggregate = pred_aggregate)
+    predict.orsf_fit(object = object,
+                     new_data = new_data,
+                     pred_horizon = t,
+                     pred_type = pred_type,
+                     na_action = na_action,
+                     boundary_checks = boundary_checks,
+                     n_thread = n_thread,
+                     verbose_progress = verbose_progress,
+                     pred_aggregate = pred_aggregate)
    }
   )
 

R/roxy.R

@@ -16,8 +16,9 @@ roxy_data_allowed <- function(){
 
 # multi-threading ---------------------------------------------------------
 
-roxy_n_thread_header <- function(){
- "(_integer_) number of threads to use. Default is one thread."
+roxy_n_thread_header <- function(action){
+ paste("(_integer_) number of threads to use while ",
+       action, ". Default is one thread.", sep = "")
 }
 
 roxy_n_thread_details <- function(){