Translated from German and added comments.

R/Comp_Statistics_Powertests_d_equal_2.R

@@ -184,7 +184,7 @@ CircComp_LP <- function(n, dim, m, kappa, index){
 }
 
 #################################################################################################
-## calculation of critical values under the null hypothesis for competing tests ## 
+## calculation of empirical critical values of competing tests under the null hypothesis ## 
 
 # replication number l (cf. main manuscript, section 6) for critical values
 reps = 20000                                                 
@@ -392,7 +392,7 @@ for (k in 1:grp_number) {
 }
 
 Power_CircComp_mixvmf_1 = data.frame("group" = Power_CircComp_mixvmf_1[,1], "n" = Power_CircComp_mixvmf_1[,2], "dim" = Power_CircComp_mixvmf_1[,3], 
-                              "Wahrscheinlichkeit" = Power_CircComp_mixvmf_1[,4], "test" = Power_CircComp_mixvmf_1[,5], "level_10" = Power_CircComp_mixvmf_1[,6], 
+                              "probability" = Power_CircComp_mixvmf_1[,4], "test" = Power_CircComp_mixvmf_1[,5], "level_10" = Power_CircComp_mixvmf_1[,6], 
                               "level_5" = Power_CircComp_mixvmf_1[,7], "level_1" = Power_CircComp_mixvmf_1[,8])
 print(Power_CircComp_mixvmf_1)
 
@@ -448,7 +448,7 @@ for (k in 1:grp_number) {
 }
 
 Power_CircComp_mixvmf_2 = data.frame("group" = Power_CircComp_mixvmf_2[,1], "n" = Power_CircComp_mixvmf_2[,2], "dim" = Power_CircComp_mixvmf_2[,3], 
-                              "Wahrscheinlichkeit" = Power_CircComp_mixvmf_2[,4], "test" = Power_CircComp_mixvmf_2[,5], "level_10" = Power_CircComp_mixvmf_2[,6], 
+                              "probability" = Power_CircComp_mixvmf_2[,4], "test" = Power_CircComp_mixvmf_2[,5], "level_10" = Power_CircComp_mixvmf_2[,6], 
                               "level_5" = Power_CircComp_mixvmf_2[,7], "level_1" = Power_CircComp_mixvmf_2[,8])
 print(Power_CircComp_mixvmf_2)
 
@@ -502,7 +502,7 @@ for (k in 1:grp_number) {
 }
 
 Power_CircComp_mixvmf_3 = data.frame("group" = Power_CircComp_mixvmf_3[,1], "n" = Power_CircComp_mixvmf_3[,2], "dim" = Power_CircComp_mixvmf_3[,3], 
-                              "Wahrscheinlichkeit" = Power_CircComp_mixvmf_3[,4], "test" = Power_CircComp_mixvmf_3[, 5], "level_10" = Power_CircComp_mixvmf_3[,6], "level_5" = Power_CircComp_mixvmf_3[,7], 
+                              "probability" = Power_CircComp_mixvmf_3[,4], "test" = Power_CircComp_mixvmf_3[, 5], "level_10" = Power_CircComp_mixvmf_3[,6], "level_5" = Power_CircComp_mixvmf_3[,7], 
                               "level_1" = Power_CircComp_mixvmf_3[,8])
 print(Power_CircComp_mixvmf_3)
 
@@ -554,7 +554,7 @@ for (k in 1:grp_number) {
 }
 
 Power_CircComp_mixvmf_4 = data.frame("group" = Power_CircComp_mixvmf_4[,1], "n" = Power_CircComp_mixvmf_4[,2], "dim" = Power_CircComp_mixvmf_4[,3], 
-                              "Wahrscheinlichkeit" = Power_CircComp_mixvmf_4[,4], "test" = Power_CircComp_mixvmf_4[,5], "level_10" = Power_CircComp_mixvmf_4[,6], "level_5" = Power_CircComp_mixvmf_4[,7], 
+                              "probability" = Power_CircComp_mixvmf_4[,4], "test" = Power_CircComp_mixvmf_4[,5], "level_10" = Power_CircComp_mixvmf_4[,6], "level_5" = Power_CircComp_mixvmf_4[,7], 
                               "level_1" = Power_CircComp_mixvmf_4[,8])
 print(Power_CircComp_mixvmf_4)