Fix docs errors

R/edge_pairs.R

@@ -1,3 +1,9 @@
+#' Find pairs of vertices that are connected in both directions
+#'
+#' @param graph An initial graph as returned by [graph_create()].
+#'
+#' @return A list of vertex pairs which are connected in both directions. NULL
+#'   if no such pairs are found
 edge_pairs <- function(graph) {
   g_names <- names(graph$hypotheses)
 

R/test_power_input_val.R

@@ -1,3 +1,53 @@
+#' Validate inputs for testing and power simulations
+#'
+#' @param graph An initial graph as returned by [graph_create()].
+#' @param p A numeric vector of p-values (unadjusted, raw), whose values should
+#'   be between 0 & 1. The length should match the number of hypotheses in
+#'   `graph`.
+#' @param alpha A numeric value of the overall significance level, which should
+#'   be between 0 & 1. The default is 0.025 for one-sided hypothesis testing
+#'   problems; another common choice is 0.05 for two-sided hypothesis testing
+#'   problems. Note when parametric tests are used, only one-sided tests are
+#'   supported.
+#' @param test_groups A list of numeric vectors specifying hypotheses to test
+#'   together. Grouping is needed to correctly perform Simes and parametric
+#'   tests.
+#' @param test_types A character vector of test types to apply to each test
+#'   group. This is needed to correctly perform Simes and parametric
+#'   tests. The length should match the number of elements in `test_groups`.
+#' @param test_corr (Optional) A list of numeric correlation matrices. Each
+#'   entry in the list should correspond to each test group. For a test group
+#'   using Bonferroni or Simes tests, its corresponding entry in `test_corr`
+#'   should be `NA`. For a test group using parametric tests, its
+#'   corresponding entry in `test_corr` should be a numeric correlation matrix
+#'   specifying the correlation between test statistics for hypotheses in this
+#'   test group. The length should match the number of elements in
+#'   `test_groups`.
+#' @param verbose A logical scalar specifying whether the details of the
+#'   adjusted p-value calculations should be included in results. When
+#'   `verbose = TRUE`, adjusted p-values are provided for each intersection
+#'   hypothesis. The default is `verbose = FALSE`.
+#' @param test_values A logical scalar specifying whether adjusted significance
+#'   levels should be provided for each hypothesis. When `test_values = TRUE`,
+#'   it provides an equivalent way of performing graphical multiple comparison
+#'   procedures by comparing each p-value with its significance level. If the
+#'   p-value of a hypothesis is less than or equal to its significance level,
+#'   the hypothesis is rejected. The default is `test_values = FALSE`.
+#' @param sim_n An integer scalar specifying the number of simulations. The
+#'   default is 1e5.
+#' @param power_marginal A numeric vector of marginal power values to use when
+#'   simulating p-values. See Details for more on the simulation process.
+#' @param success A list of user-defined functions to specify the success
+#'   criteria. Functions must take one simulation's logical vector of results as
+#'   an input, and return a length-one logical vector. For instance, if
+#'   "success" means rejecting hypotheses 1 and 2, use `sim_success = list("1
+#'   and 2" = function(x) x[1] && x[2])`. If the list is not named, the function
+#'   body will be used as the name. Lambda functions also work starting with R
+#'   4.1, e.g. `sim_success = list(\(x) x[3] || x[4])`.
+#'
+#' @return Returns `graph` invisibly
+#'
+#' @rdname input_val
 test_input_val <- function(graph,
                            p,
                            alpha,
@@ -94,6 +144,7 @@ test_input_val <- function(graph,
   invisible(graph)
 }
 
+#' @rdname input_val
 power_input_val <- function(graph, sim_n, power_marginal, test_corr, success) {
   num_hyps <- length(graph$hypotheses)