minor improvements

R/ANOVA.R

@@ -1,6 +1,6 @@
 #' @title `r ANOVA$private_fields$.name`
 #' 
-#' @description Performs F statistic based k sample permutation test on data vectors. 
+#' @description Performs F statistic based k sample permutation test on data vectors.
 #' 
 #' @aliases ksample.anova
 #' 
@@ -15,11 +15,11 @@ ANOVA <- R6Class(
     inherit = KSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `ANOVA` object. 
+        #' @description Create a new `ANOVA` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `ANOVA` object. 
+        #' @return A `ANOVA` object.
         initialize = function(
             type = c("permu", "asymp"),
             n_permu = 0L

R/AnsariBradley.R

@@ -1,6 +1,6 @@
 #' @title `r AnsariBradley$private_fields$.name`
 #' 
-#' @description Performs two sample Ansari-Bradley test on data vectors. 
+#' @description Performs two sample Ansari-Bradley test on data vectors.
 #' 
 #' @aliases twosample.ansari
 #' 
@@ -15,11 +15,11 @@ AnsariBradley <- R6Class(
     inherit = TwoSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `AnsariBradley` object. 
+        #' @description Create a new `AnsariBradley` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `AnsariBradley` object. 
+        #' @return A `AnsariBradley` object.
         initialize = function(
             type = c("permu", "asymp"),
             alternative = c("two_sided", "less", "greater"), n_permu = 0L

R/CDF.R

@@ -1,6 +1,6 @@
 #' @title `r CDF$private_fields$.name`
 #' 
-#' @description Performs statistical inference on population cdf. 
+#' @description Performs statistical inference on population cdf.
 #' 
 #' @aliases onesample.cdf
 #' 
@@ -15,7 +15,7 @@ CDF <- R6Class(
     inherit = OneSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `CDF` object. 
+        #' @description Create a new `CDF` object.
         #' 
         #' @param conf_level a number specifying confidence level of the confidence bounds.
         #' 
@@ -24,11 +24,11 @@ CDF <- R6Class(
             super$initialize(conf_level = conf_level)
         },
 
-        #' @description Plot the estimate and confidence bounds for population cdf of the data. 
+        #' @description Plot the estimate and confidence bounds for population cdf of the data.
         #' 
         #' @template plot_params
         #' 
-        #' @return The object itself (invisibly). 
+        #' @return The object itself (invisibly).
         plot = function(style = c("graphics", "ggplot2")) {
             private$.type <- "permu"
             super$plot(style = style)

R/ChiSquare.R

@@ -1,6 +1,6 @@
 #' @title `r ChiSquare$private_fields$.name`
 #' 
-#' @description Performs chi-square statistic based permutation test on contingency tables. 
+#' @description Performs chi-square statistic based permutation test on contingency tables.
 #' 
 #' @aliases table.chisq
 #' 
@@ -15,11 +15,11 @@ ChiSquare <- R6Class(
     inherit = ContingencyTableTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `ChiSquare` object. 
+        #' @description Create a new `ChiSquare` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `ChiSquare` object. 
+        #' @return A `ChiSquare` object.
         initialize = function(
             type = c("permu", "asymp"),
             n_permu = 0L

R/ContingencyTableTest.R

@@ -1,6 +1,6 @@
 #' @title ContingencyTableTest Class
 #' 
-#' @description This class specializes `PermuTest` for permutation tests for contingency tables. Note that it is not recommended to create objects of this class directly. 
+#' @description This class specializes `PermuTest` for permutation tests for contingency tables. Note that it is not recommended to create objects of this class directly.
 #' 
 #' 
 #' @export

R/Correlation.R

@@ -1,6 +1,6 @@
 #' @title `r Correlation$private_fields$.name`
 #' 
-#' @description Performs correlation coefficient based two sample permutation test on data vectors. 
+#' @description Performs correlation coefficient based two sample permutation test on data vectors.
 #' 
 #' @aliases association.corr
 #' 
@@ -15,12 +15,12 @@ Correlation <- R6Class(
     inherit = TwoSampleAssociationTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `Correlation` object. 
+        #' @description Create a new `Correlation` object.
         #' 
         #' @template init_params
-        #' @param method a character string indicating which correlation coefficient is to be computed. 
+        #' @param method a character string indicating which correlation coefficient is to be computed.
         #' 
-        #' @return A `Correlation` object. 
+        #' @return A `Correlation` object.
         initialize = function(
             type = c("permu", "asymp"), method = c("pearson", "kendall", "spearman"),
             alternative = c("two_sided", "less", "greater"), n_permu = 0L

R/Difference.R

@@ -1,6 +1,6 @@
 #' @title `r Difference$private_fields$.name`
 #' 
-#' @description Performs mean based two sample permutation test on data vectors. 
+#' @description Performs mean based two sample permutation test on data vectors.
 #' 
 #' @aliases twosample.difference
 #' 
@@ -14,11 +14,11 @@ Difference <- R6Class(
     inherit = TwoSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `Difference` object. 
+        #' @description Create a new `Difference` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `Difference` object. 
+        #' @return A `Difference` object.
         initialize = function(
             method = c("mean", "median"),
             alternative = c("two_sided", "less", "greater"), n_permu = 0L

R/Friedman.R

@@ -1,6 +1,6 @@
 #' @title `r Friedman$private_fields$.name`
 #' 
-#' @description Performs Friedman test on data for a randomized complete block design. 
+#' @description Performs Friedman test on data for a randomized complete block design.
 #' 
 #' @aliases rcbd.friedman
 #' 
@@ -15,11 +15,11 @@ Friedman <- R6Class(
     inherit = RCBD,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `Friedman` object. 
+        #' @description Create a new `Friedman` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `Friedman` object. 
+        #' @return A `Friedman` object.
         initialize = function(
             type = c("permu", "asymp"),
             n_permu = 0L

R/JonckheereTerpstra.R

@@ -1,6 +1,6 @@
 #' @title `r JonckheereTerpstra$private_fields$.name`
 #' 
-#' @description Performs k sample Jonckheere-Terpstra Test on data vectors. 
+#' @description Performs k sample Jonckheere-Terpstra Test on data vectors.
 #' 
 #' @aliases ksample.jt
 #' 
@@ -15,11 +15,11 @@ JonckheereTerpstra <- R6Class(
     inherit = KSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `JonckheereTerpstra` object. 
+        #' @description Create a new `JonckheereTerpstra` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `JonckheereTerpstra` object. 
+        #' @return A `JonckheereTerpstra` object.
         initialize = function(
             type = c("permu", "asymp"),
             alternative = c("two_sided", "less", "greater"), n_permu = 0L

R/KSampleTest.R

@@ -1,6 +1,6 @@
 #' @title KSampleTest Class
 #' 
-#' @description This class specializes `PermuTest` for k sample permutation tests. Note that it is not recommended to create objects of this class directly. 
+#' @description This class specializes `PermuTest` for k sample permutation tests. Note that it is not recommended to create objects of this class directly.
 #' 
 #' 
 #' @export

R/KolmogorovSmirnov.R

@@ -1,6 +1,6 @@
 #' @title `r KolmogorovSmirnov$private_fields$.name`
 #' 
-#' @description Performs two sample Kolmogorov-Smirnov test on data vectors. 
+#' @description Performs two sample Kolmogorov-Smirnov test on data vectors.
 #' 
 #' @aliases twosample.ks
 #' 
@@ -14,11 +14,11 @@ KolmogorovSmirnov <- R6Class(
     inherit = TwoSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `KolmogorovSmirnov` object. 
+        #' @description Create a new `KolmogorovSmirnov` object.
         #' 
         #' @template init_params
         #' 
-        #' @return A `KolmogorovSmirnov` object. 
+        #' @return A `KolmogorovSmirnov` object.
         initialize = function(n_permu = 0L) {
             super$initialize(alternative = "greater", n_permu = n_permu)
         }
@@ -30,10 +30,11 @@ KolmogorovSmirnov <- R6Class(
             m <- length(private$.data$x)
             n <- length(private$.data$y)
 
-            tmp <- rep.int(1 / m, m + n)
+            geq_m <- -1 / n
+            leq_m <- rep.int(1 / m, m + n)
             private$.statistic_func <- function(x, y) {
-                max(abs(cumsum(`[<-`(tmp, order(c(x, y)) <= m, -1 / n))))
+                max(abs(cumsum(`[<-`(leq_m, order(c(x, y)) > m, geq_m))))
             }
         }
     )
-)
+)

R/KruskalWallis.R

@@ -1,6 +1,6 @@
 #' @title `r KruskalWallis$private_fields$.name`
 #' 
-#' @description Performs k sample Kruskal-Wallis Test on data vectors. 
+#' @description Performs k sample Kruskal-Wallis Test on data vectors.
 #' 
 #' @aliases ksample.kw
 #' 
@@ -15,12 +15,12 @@ KruskalWallis <- R6Class(
     inherit = KSampleTest,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `KruskalWallis` object. 
+        #' @description Create a new `KruskalWallis` object.
         #' 
         #' @template init_params
-        #' @param type a character string specifying the way to calculate p-values, must be one of `"permu"` (default) or `"asymp"`. 
+        #' @param type a character string specifying the way to calculate p-values, must be one of `"permu"` (default) or `"asymp"`.
         #' 
-        #' @return A `KruskalWallis` object. 
+        #' @return A `KruskalWallis` object.
         initialize = function(
             type = c("permu", "asymp"),
             n_permu = 0L, scoring = c("rank", "vw", "expon")

R/MultiCompT.R

@@ -1,6 +1,6 @@
 #' @title `r MultiCompT$private_fields$.name`
 #' 
-#' @description Performs t statistic based multiple comparison on data vectors. 
+#' @description Performs t statistic based multiple comparison on data vectors.
 #' 
 #' @aliases multicomp.t
 #' 
@@ -15,28 +15,25 @@ MultiCompT <- R6Class(
     inherit = MultipleComparison,
     cloneable = FALSE,
     public = list(
-        #' @description Create a new `MultiCompT` object. 
+        #' @description Create a new `MultiCompT` object.
         #' 
         #' @template init_params
-        #' @param conf_level a numeric value between zero and one giving the family-wise confidence level to use. 
-        #' @param bonferroni a logical indicating whether to apply bonferroni adjustment. 
+        #' @param conf_level a numeric value between zero and one giving the family-wise confidence level to use.
         #' 
         #' @return A `MultiCompT` object. 
         initialize = function(
-            type = c("permu", "asymp"), bonferroni = TRUE,
+            type = c("permu", "asymp"), method = c("bonferroni", "no_bonferroni"),
             conf_level = 0.95, n_permu = 0L, scoring = c("none", "rank", "vw", "expon")
         ) {
             private$.type <- match.arg(type)
-            private$.bonferroni <- bonferroni
-            
+            private$.method <- match.arg(method)
+
             super$initialize(conf_level = conf_level, n_permu = n_permu, scoring = match.arg(scoring))
         }
     ),
     private = list(
         .name = "Multiple Comparison Based on t Statistic",
 
-        .bonferroni = NULL,
-
         .define = function() {
             lengths <- vapply(
                 X = split(private$.data, names(private$.data)),
@@ -77,13 +74,9 @@ MultiCompT <- R6Class(
         },
 
         .calculate_extra = function() {
-            super$.calculate_extra()
-
-            if (private$.bonferroni) {
-                private$.multicomp$differ <- (
-                    private$.p_value < (1 - private$.conf_level) / nrow(private$.multicomp)
-                )
-            }
+            private$.differ <- private$.p_value < (1 - private$.conf_level) / (
+                if (private$.method == "bonferroni") length(private$.p_value) else 1
+            )
         }
     )
 )