Wilcoxonank Sum Statistic Distribution in R (4 Examples) | dwilcox, pwilcox, qwilcox & rwilcox Functions
This article illustrates how to apply the Wilcoxonank Sum Statistic functions in the R programming language.
The table of content is structured as follows:
- Example 1: Wilcoxonank Sum Statistic Probability Density Function (dwilcox Function)
- Example 2: Wilcoxonank Sum Statistic Cumulative Distribution Function (pwilcox Function)
- Example 3: Wilcoxonank Sum Statistic Quantile Function (qwilcox Function)
- Example 4: Generating Random Numbers (rwilcox Function)
- Video & Further Resources
Let’s dive into it.
Example 1: Wilcoxonank Sum Statistic Probability Density Function (dwilcox Function)
The following R code shows how to draw a graph illustrating the probability density function (PDF) of the Wilcoxonank Sum Statistic:
x_dwilcox <- seq(0, 100, by = 1) # Specify x-values for dwilcox function y_dwilcox <- dwilcox(x_dwilcox, m = 50, n = 20) # Apply dwilcox function plot(y_dwilcox, type = "o") # Plot dwilcox values

Figure 1: PDF of Wilcoxonank Sum Statistic.
Example 2: Wilcoxonank Sum Statistic Cumulative Distribution Function (pwilcox Function)
This example explains how to draw a graphic of the cumulative distribution function (CDF) of the Wilcoxonank Sum Statistic:
x_pwilcox <- seq(0, 100, by = 1) # Specify x-values for pwilcox function y_pwilcox <- pwilcox(x_pwilcox, m = 50, n = 20) # Apply pwilcox function plot(y_pwilcox, type = "o") # Plot pwilcox values

Figure 2: CDF of Wilcoxonank Sum Statistic.
Example 3: Wilcoxonank Sum Statistic Quantile Function (qwilcox Function)
This example shows how to create a graphic of the quantile function of the Wilcoxonank Sum Statistic:
x_qwilcox <- seq(0, 1, by = 0.01) # Specify x-values for qwilcox function y_qwilcox <- qwilcox(x_qwilcox, m = 50, n = 20) # Apply qwilcox function plot(y_qwilcox, type = "o") # Plot qwilcox values

Figure 3: Quantile Function of Wilcoxonank Sum Statistic.
Example 4: Generating Random Numbers (rwilcox Function)
The last example illustrates how to generate random numbers according to the Wilcoxonank Sum Statistic:
set.seed(98989) # Set seed for reproducibility N <- 100000 # Specify sample size y_rwilcox <- rwilcox(N, m = 50, n = 20) # Draw N random values y_rwilcox # Print values to RStudio console hist(y_rwilcox, # Plot of randomly drawn density breaks = 50, main = "")

Figure 4: Random Number According to Wilcoxonank Sum Statistic.
Video & Further Resources
I have recently released a video instruction on my YouTube channel, which shows the R codes of this tutorial. You can find the video below:
The YouTube video will be added soon.
You might also have a look at the other tutorials on distributions and the simulation of random numbers in R:
- Bernoulli Distribution in R
- Beta Distribution in R
- Binomial Distribution in R
- Bivariate & Multivariate Distributions in R
- Cauchy Distribution in R
- Chi-Squred Distribution in R
- Exponential Distribution in R
- F Distribution in R
- Gamma Distribution in R
- Geometric Distribution in R
- Hypergeometric Distribution in R
- Log Normal Distribution in R
- Logistic Distribution in R
- Negative Binomial Distribution in R
- Normal Distribution in R
- Poisson Distribution in R
- Student t Distribution in R
- Studentized Range Distribution in R
- Uniform Distribution in R
- Weibull Distribution in R
- Wilcoxon Signedank Statistic Distribution in R
- Wilcoxonank Sum Statistic Distribution in R
Additionally, you may want to read the related tutorials of my website:
This article explained how to use the dwilcox, pwilcox, qwilcox, and rwilcox functions in the R programming language. Don’t hesitate to tell me about it in the comments, in case you have further questions.
Subscribe to the Statistics Globe Newsletter
Get regular updates on the latest tutorials, offers & news at Statistics Globe.
I hate spam & you may opt out anytime: Privacy Policy.
Thank you!
Please check your email inbox and click the confirmation link to complete your subscription. If you don’t see the email within a few minutes, please also check your spam/junk folder.
I’m Joachim Schork. On this website, I provide statistics tutorials as well as code in Python and R programming.
Statistics Globe Newsletter
Get regular updates on the latest tutorials, offers & news at Statistics Globe. I hate spam & you may opt out anytime: Privacy Policy.
Thank you!
Please check your email inbox and click the confirmation link to complete your subscription. If you don’t see the email within a few minutes, please also check your spam/junk folder.






