minor docs

R/p_direction.R

@@ -50,7 +50,7 @@
 #' with an equal posterior mass of positive and negative values. Values close to
 #' 0.5 _cannot_ be used to support the null hypothesis (that the parameter does
 #' _not_ have a direction) is a similar why to how large p-values cannot be used
-#' to support the null hypothesis (see [`pd_tp_p()`]; Makowski et al., 2019).
+#' to support the null hypothesis (see [`pd_to_p()`]; Makowski et al., 2019).
 #' \cr\cr
 #' **For a discrete parameter space or a parameter space that is a mixture
 #' between discrete and continuous spaces**, exact values of 0 (or any point
@@ -75,7 +75,7 @@
 #' the larger of the two. This "simple" method is the most straightforward, but
 #' its precision is directly tied to the number of posterior draws.
 #' \cr\cr
-#' The second approach relies on [`density estimation()`]: It starts by
+#' The second approach relies on [density estimation][estimate_density]: It starts by
 #' estimating the continuous-smooth density function (for which many methods are
 #' available), and then computing the [area under the curve][area_under_curve]
 #' (AUC) of the density curve on either side of `null` and taking the maximum