The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs![12 blog posts from 2022 that deserve a second look](https://blogs.sas.com/content/iml/files/2022/03/GaussNewton2-500x336.png)
In a previous article, I presented some of the most popular blog posts from 2022. In general, popular articles deal with elementary topics that have broad appeal. However, I also write articles about advanced topics. The following articles didn't make the Top 10 list, but they deserve a second look.
![Installing R for SAS IML in SAS Viya](https://blogs.sas.com/content/iml/files/2023/01/SAS-VIY-250x200-graphic1.jpg)
Since 2008, SAS has supported an interface for calling R from the SAS/IML matrix language. Many years ago, I wrote blog posts that describe how to call R from PROC IML. For SAS 9.4, the process of installing R and calling R from PROC IML is documented in the SAS/IML
![Top 10 posts from The DO Loop in 2022](https://blogs.sas.com/content/iml/files/2022/03/missingHeatmap4-640x336.png)
Last year, I wrote almost 90 articles for The DO Loop blog. My most popular articles were about SAS programming, data visualization, statistics and data analysis, and matrix computations. If you missed these articles when I published them—or if you want to read them again!— here is the "Reader's Choice
![Working with combinations in SAS](https://blogs.sas.com/content/iml/files/2022/12/allcomb3-530x336.png)
A colleague posted a Christmas-themed code snippet that shows how to use the DATA step in SAS to output all the possible ways that Santa can hitch up a team of reindeer to pull his sled. The assumption is that Rudolph must lead the team, and the remaining reindeer are
![Construct heterogeneous structured covariance matrices in SAS ARH(1) covariance structure](https://blogs.sas.com/content/iml/files/2022/12/covstructARH1.png)
A previous article describes how to use SAS IML software to construct common covariance structures that are encountered in mixed models. Each covariance matrix has several parameters, and you want to construct a matrix for any choice of the parameters. After you have constructed the covariance matrix, you can use
![Properties of the Hadamard product](https://blogs.sas.com/content/iml/files/2017/01/ProgrammingTips-2.png)
I always emphasize efficiency in statistical programming. I have previously written about why you should never multiply with a large diagonal matrix in the SAS IML language. The reason is that it is more efficient to use elementwise multiplication than matrix multiplication. Specifically, if d is a column vector, then