The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
A SAS customer wrote, "I have access to PROC IML through SAS OnDemand for Academics. What is the best way for me to learn to program in the SAS/IML language? How do I get started with PROC IML?" That is an excellent question, and I'm happy to offer some suggestions.
Unless you diligently read the "What's New" chapter for each release of SAS software, it is easy to miss new features that appear in the language. People who have been writing SAS/IML programs for decades are sometimes surprised when I tell them about a useful new function or programming feature.
In a previous blog post, I described how to generate combinations in SAS by using the ALLCOMB function in SAS/IML software. The ALLCOMB function in Base SAS is the equivalent function for DATA step programmers. Recall that a combination is a unique arrangement of k elements chosen from a set
Have you written a SAS/IML program that you think is particularly clever? Are you the proud author of SAS/IML functions that extend the functionality of SAS software? You've worked hard to develop, debug, and test your program, so why not share it with others? There is now a location for
In my four years of blogging, the post that has generated the most comments is "How to handle negative values in log transformations." Many people have written to describe data that contain negative values and to ask for advice about how to log-transform the data. Today I describe a transformation
A colleague asked me an interesting question: I have a journal article that includes sample quantiles for a variable. Given a new data value, I want to approximate its quantile. I also want to simulate data from the distribution of the published data. Is that possible? This situation is common.