The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs![Popular! Articles that strike a chord with SAS users](https://blogs.sas.com/content/iml/files/2017/01/AdvancedAnalytics-2.png)
I blog about a lot of topics, but the following five categories represent some of my favorite subjects. Judging by the number of readers and comments, these articles have struck a chord with SAS users. If you haven't read them, check them out. (If you HAVE read them, some are
![Functions to know: The MEAN, VAR, and STD functions](https://blogs.sas.com/content/iml/files/2012/03/t_desc1.png)
As a SAS developer, I am always looking ahead to the next release of SAS. However, many SAS customer sites migrate to new releases slowly and are just now adopting versions of SAS that were released in 2010 or 2011. Consequently, I want to write a few articles that discuss
![How to compute Mahalanobis distance in SAS](https://blogs.sas.com/content/iml/files/2012/02/computemahal1.png)
I recently blogged about Mahalanobis distance and what it means geometrically. I also previously showed how Mahalanobis distance can be used to compute outliers in multivariate data. But how do you compute Mahalanobis distance in SAS? Computing Mahalanobis distance with built-in SAS procedures and functions There are several ways to
![What is Mahalanobis distance? What is Mahalanobis distance?](https://blogs.sas.com/content/iml/files/2012/02/mahal.png)
I previously described how to use Mahalanobis distance to find outliers in multivariate data. This article takes a closer look at Mahalanobis distance. A subsequent article will describe how you can compute Mahalanobis distance. Distance in standard units In statistics, we sometimes measure "nearness" or "farness" in terms of the
![Use the Cholesky transformation to correlate and uncorrelate variables Use the Cholesky transformation to correlate and uncorrelate variables](https://blogs.sas.com/content/iml/files/2012/02/choleskytransform1.png)
A variance-covariance matrix expresses linear relationships between variables. Given the covariances between variables, did you know that you can write down an invertible linear transformation that "uncorrelates" the variables? Conversely, you can transform a set of uncorrelated variables into variables with given covariances. The transformation that works this magic is
![Rounding up, rounding down Rounding up and rounding down in SAS](https://blogs.sas.com/content/iml/files/2011/10/t_round3.png)
SAS has several ways to round a number to an integer. You can round a number up, round it down, or round it to the nearest integer. If your data contain both positive and negative values, you can also round numbers toward zero, or away from zero. The functions that