In ralphjia/wilcoxon:

Some example usage of the wilcoxon_test() function:

library(wilcoxon)
x <- c(1.83,  0.50,  1.62,  2.48, 1.68, 1.88, 1.55, 3.06, 1.30)
y <- c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)

Wilcoxon Signed-Rank Examples:

wilcoxon_test(x)
wilcoxon_test(x, y, paired = T, alternative = 'g')
wilcoxon_test(x, y, paired = T, alternative = 'g', exact = F) # Notice the slight difference in p-value

Wilcoxon Rank-Sum Examples:

wilcoxon_test(x, y, paired = F, alternative = 'g')
wilcoxon_test(x, y, paired = F, alternative = 'l', exact = F) 
wilcoxon_test(x, y, paired = F, alternative = 'l', exact = F, correct = F) # Again, notice the slight difference in p-value

Structure of the return value:

value <- wilcoxon_test(x, y, paired = F, alternative = 'g')
str(value)

As we can see, the return value is a list of class "htest" consisting of the test statistic, the distribution parameter (which will always be NULL for a Wilcoxon test), the p-value, the null value (equal to mu), the alternative hypothesis, the method applied, and the name of the data that was supplied.

Demonstration of the accuracy of the results of wilcoxon_test() by comparison to wilcox.test():

all.equal(wilcoxon_test(x), wilcox.test(x))
all.equal(wilcoxon_test(x, y, paired = T, alternative = 'g'), wilcox.test(x, y, paired = T, alternative = 'g'))
all.equal(wilcoxon_test(x, y, paired = T, alternative = 'g', exact = F), wilcox.test(x, y, paired = T, alternative = 'g', exact = F))
all.equal(wilcoxon_test(x, y, paired = F, alternative = 'l', exact = F), wilcox.test(x, y, paired = F, alternative = 'l', exact = F))
all.equal(wilcoxon_test(x, y, paired = F, alternative = 'l', exact = F, correct = F), wilcoxon_test(x, y, paired = F, alternative = 'l', exact = F, correct = F))

Comparison of efficiency against wilcox.test():

set.seed(1)
a <- rnorm(500)
b <- rnorm(500)
comparison1 <- bench::mark(wilcoxon_test(a, exact = F), wilcox.test(a, exact = F)) # Wilcoxon Signed-Rank Test Comparison
comparison2 <- bench::mark(wilcoxon_test(a, b, paired = F, exact = F), wilcox.test(a, b, paired = F, exact = F)) # Wilcoxon Rank-Sum Test Comparison
summary(comparison1)