fix: Add missing permutation MAA param

R/MutualImpurityReduction.R

@@ -52,6 +52,7 @@ MutualImpurityReduction <- function(REL) {
 #' @param p.threshold (Default = 0.01) P-value threshold
 #' @param method The method to use. One of: `"Janitza"` or `"Permutation"`.
 #' @param permutation.num (If method is `"Permutation"`) Number of AIR permutations to determine p-value. (Default: 100)
+#' @param permutation.MeanAdjustedAgreement If method is `"Permutation"` and `MIR` used `MeanAdjustedAgreement`.
 #'
 #' @returns A list:
 #'  * `method`: The method used.
@@ -64,7 +65,8 @@ MutualImpurityReductionVariableSelection <- function(
     MIR,
     p.threshold = 0.01,
     method = c("Janitza", "Permutation"),
-    permutation.num = 100
+    permutation.num = 100,
+    permutation.MeanAdjustedAgreement = NULL
 ) {
   if (!inherits(MIR, "MutualImpurityReduction")) {
     stop("`MIR` must be a `MutualImpurityReduction` object.")
@@ -80,6 +82,7 @@ MutualImpurityReductionVariableSelection <- function(
     "Permutation" = MIR_VarSel_Permutation(
       MIR = MIR,
       p.threshold = 0.01,
+      perm = permutation.MeanAdjustedAgreement,
       num.permutations = permutation.num
     ),
   )

man/MutualImpurityReductionVariableSelection.Rd

@@ -8,7 +8,8 @@ MutualImpurityReductionVariableSelection(
   MIR,
   p.threshold = 0.01,
   method = c("Janitza", "Permutation"),
-  permutation.num = 100
+  permutation.num = 100,
+  permutation.MeanAdjustedAgreement = NULL
 )
 }
 \arguments{
@@ -19,6 +20,8 @@ MutualImpurityReductionVariableSelection(
 \item{method}{The method to use. One of: \code{"Janitza"} or \code{"Permutation"}.}
 
 \item{permutation.num}{(If method is \code{"Permutation"}) Number of AIR permutations to determine p-value. (Default: 100)}
+
+\item{permutation.MeanAdjustedAgreement}{If method is \code{"Permutation"} and \code{MIR} used \code{MeanAdjustedAgreement}.}
 }
 \value{
 A list:

tests/testthat/test-MutualImpurityReduction.R

@@ -74,19 +74,19 @@ test_that("MAA-MIR", {
   p.mir <- MutualImpurityReductionVariableSelection(
     mir,
     method = "Permutation",
-    # perm = MeanAdjustedAgreement(
-    #   RandomForestSurrogates(
-    #     x = SMD_example_data[, -1],
-    #     y = SMD_example_data[, 1],
-    #     num.trees = 100,
-    #     importance = "impurity_corrected",
-    #     permutate = TRUE,
-    #     num.threads = 1,
-    #     seed = 1964531019, # set.seed(42);runif(1,0,.Machine$integer.max)
-    #     s = 10
-    #   ),
-    #   t = 5, num.threads = 1
-    # ),
+    permutation.MeanAdjustedAgreement = MeanAdjustedAgreement(
+      RandomForestSurrogates(
+        x = SMD_example_data[, -1],
+        y = SMD_example_data[, 1],
+        num.trees = 100,
+        importance = "impurity_corrected",
+        permutate = TRUE,
+        num.threads = 1,
+        seed = 1964531019, # set.seed(42);runif(1,0,.Machine$integer.max)
+        s = 10
+      ),
+      t = 5, num.threads = 1
+    ),
     permutation.num = 100,
     p.t = 0.01
   )