Writing vignette for dig function

R/dig.R

@@ -70,6 +70,15 @@
 #' - `support`: a numeric scalar value of relative frequency of rows satisfying \eqn{C},
 #'   \eqn{supp = sum / |R|}.
 #'
+#' - `indices`: an integer vector of row indices of rows satisfying \eqn{C} for
+#'   logical data, or the indices of rows with non-zero truth degrees for fuzzy
+#'   data, \eqn{indices = \{r \in R : \mu_C(r) > 0\}}.
+#'
+#' - `weights`: a numeric vector of truth degrees of \eqn{C} for each row in
+#'   \eqn{R}, \eqn{weights[r] = \mu C(r)}. Logical data is treated as a special
+#'   case of fuzzy data, where \eqn{\mu_C(r)} is 1 for rows satisfying \eqn{C}
+#'   and 0 otherwise.
+#'
 #' - `pp`, `pn`, `np`, `nn`: a numeric vector of entries of a contingency table
 #'   for \eqn{C} and \eqn{F}, satisfying the Ruspini condition
 #'   \eqn{pp + pn + np + nn = |R|}.

_pkgdown.yml

@@ -15,6 +15,7 @@ articles:
       - nuggets
       - data-preparation
       - association-rules
+      - custom-patterns
 
 reference:
   - title: "Data Preparation"

vignettes/association-rules.Rmd

@@ -147,7 +147,7 @@ to_logical <- function(x) {
 In many applications, you want to constrain which predicates can appear on
 each side of the rule. This is done with the `antecedent` and `consequent`
 arguments, which accept
-[tidyselect](https://tidyselect.r-lib.org/articles/syntax.html) expressions.
+[tidyselect expression](https://tidyselect.r-lib.org/reference/language.html) expressions.
 
 For example, to find rules that predict the `uptake` rate from all other
 variables:
@@ -453,3 +453,6 @@ This vignette demonstrated how to search for association rules using the
 For further details, consult the function documentation:
 `dig_associations()`, `add_interest()`, `dig_tautologies()`,
 `parse_condition()`, `partition()`, `var_names()`.
+
+For more advanced usage with custom pattern types, see
+`vignette("custom-patterns")`.