Fix anchors

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.9.4
-Date: 2024-03-05 20:08:55 UTC
-SHA: b37e486d06a918ee94396145561ed41d61cd56c6
+Version: 0.9.5
+Date: 2024-06-21 21:43:10 UTC
+SHA: 3a818425e8a7aedd8a407710b5d85bcad33fc9e8

R/geom_split_violin.R

@@ -9,8 +9,8 @@
 #' Trang Q. Nguyen for adding the nudge parameter.
 #'
 #' @inheritParams ggplot2::geom_violin
-#' @param stat Use to override the default connection between [geom_violin()]
-#' and [stat_ydensity()].
+#' @param stat Use to override the default connection between [ggplot2::geom_violin()]
+#' and [ggplot2::stat_ydensity()].
 #' @param nudge Add space between the half-violin and the middle of the space
 #' allotted to a given factor on the x-axis.
 #' @returns a [`ggplot2::layer`] object

R/maxent.R

@@ -1,6 +1,6 @@
 #' MaxEnt model
 #'
-#' [maxent] defines the MaxEnt model as used in Species
+#' `maxent` defines the MaxEnt model as used in Species
 #' Distribution Models.
 #' A good guide to how options of a MaxEnt model work can be found in
 #' https://onlinelibrary.wiley.com/doi/full/10.1111/j.1600-0587.2013.07872.x
@@ -12,7 +12,7 @@
 #' @param feature_classes character, continuous feature classes desired, either
 #'   "default" or any subset of "lqpht" (for example, "lh")
 #' @param regularization_multiplier  numeric, a constant to adjust regularization
-#' @returns a [`model_spec`] for a `maxent` model
+#' @returns a [`parsnip::model_spec`] for a `maxent` model
 #' @examples
 #' \donttest{
 #' # format the data

R/predict_raster.R

@@ -1,8 +1,8 @@
 #' Make predictions for a whole raster
 #'
 #' This function allows to use a raster as data to make predictions from a
-#' variety of [tidymodels] objects, such as [`simple_ensemble`] or `stacks::linear_stack`
-#' @param object the [`tidymodels`] object of interest
+#' variety of `tidymodels` objects, such as [`simple_ensemble`] or [`stacks::stacks`]
+#' @param object the `tidymodels` object of interest
 #' @param raster the [`terra::SpatRaster`] with the input data. It has to include
 #' levels with the same names as the variables used in `object`
 #' @param ... parameters to be passed to the standard `predict()` function

R/prob_metrics.R

@@ -3,7 +3,7 @@
 #' `tidysdm` provides specialised metrics for SDMs, which have their own
 #' help pages([boyce_cont()], [kap_max()], and [tss_max()]). Additionally, it also 
 #' provides methods to handle [sf::sf] objects for the following
-#' standard [yardstick] metrics:
+#' standard `yardstick` metrics:
 #' 
 #' Note that `roc_aunp` and `roc_aunu` are multiclass metrics, and as such are
 #' are not relevant for SDMs (which work on a binary response). They are included

R/recipe_sf.R

@@ -21,7 +21,7 @@
 #' @param x An [sf::sf] data frame.
 #' @param ... parameters to be passed to [recipes::recipe()]
 #' @returns An object of class `spatial_recipe`, which is a derived version of
-#'  [recipes::recipe] , see
+#'  [recipes::recipe()] , see
 #' the manpage for [recipes::recipe()] for details.
 #' @export
 #' @import recipes

R/spatial_initial_split.R

@@ -1,11 +1,11 @@
 #' Simple Training/Test Set Splitting for spatial data
 #'
 #' `spatial_initial_split` creates a single binary split of the data into a training
-#'  set and testing set. All strategies from the package [spatialsample] are available;
+#'  set and testing set. All strategies from the package `spatialsample` are available;
 #'  a random split from that strategy will be used to generate the initial split.
 #' @param data A dataset (data.frame or tibble)
 #' @param prop The proportion of data to be retained for modelling/analysis.
-#' @param strategy A sampling strategy from [spatialsample]
+#' @param strategy A sampling strategy from `spatialsample`
 #' @param ... parameters to be passed to the `strategy`
 #' @returns An `rsplit` object that can be used with the [rsample::training] and [rsample::testing]
 #'  functions to extract the data in each split.

cran-comments.md

@@ -1,4 +1,5 @@
-This is a minor update, adding a few methods and improving the vignettes.
+This is a resubmission. The previous version raised a problem of some missing package
+anchors. All documentation should not include the required package anchors.
 
 ## Test environments
 - R-hub linux (r-devel)