QR Matrix Decomposition in R (Example) | Factorization with qr() Function
In this article, I’ll show how to perform a QR matrix decomposition (also called QR factorization or QU factorization) using the qr() function in R programming.
Table of contents:
Here’s the step-by-step process…
Creation of Exemplifying Data
I use the following data matrix as basement for this tutorial:
set.seed(9823633) # Create random example matrix my_mat <- matrix(runif(12), nrow = 4) my_mat # Print example matrix
As you can see based on Table 1, our example data is a matrix composed of four rows and three variables.
For this tutorial, we also have to create a vector:
my_vec <- 1:4 # Create vector my_vec # Print vector # [1] 1 2 3 4
The previous output shows our vector in the RStudio console. It consists of four integer elements ranging from 1 to 4.
Example: QR Decomposition of Matrix Using qr() & solve() Functions
The following code explains how to use conduct a QR decomposition in R.
For this task, we have to apply the solve and qr functions as shown below:
solve(qr(my_mat), my_vec) # Apply qr() & solve() # [1] 3.0006847 0.6967126 5.2930560
The previous output shows our result, i.e. a vector containing three numeric values.
Video, Further Resources & Summary
In case you need more info on the topics of this post, you could have a look at the following video on the Statistics Globe YouTube channel. In the video, I’m illustrating the content of this page:
The YouTube video will be added soon.
Furthermore, you might have a look at some of the related tutorials on this website.
- Solve System of Equations in R
- Multiply Rows of Matrix by Vector in R
- Inverse of Matrix in R
- Useful Functions in R
- R Programming Language
At this point you should have learned how to apply the qr() function in R programming. If you have further questions or comments, please let me know in the comments section below. Furthermore, please subscribe to my email newsletter in order to receive updates on new tutorials.