Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
You can extend the capability of the SAS/IML language by writing modules. A module is a user-defined function. You can define a module by using the START and FINISH statements. Many people, including myself, define modules at the top of the SAS/IML program in which they are used. You can
Do you know someone who has a birthday in mid-September? Odds are that you do: the middle of September is when most US babies are born, according to data obtained from the National Center for Health Statistics (NCHS) Web site (see Table 1-16). There's an easy way to remember this
Looping is essential to statistical programming. Whether you need to iterate over parameters in an algorithm or indices in an array, a loop is often one of the first programming constructs that a beginning programmer learns. Today is the first anniversary of this blog, which is named The DO Loop,
My elderly mother enjoys playing Scrabble®. The only problem is that my father and most of my siblings won't play with her because she beats them all the time! Consequently, my mother is always excited when I visit because I'll play a few Scrabble games with her. During a recent
I previously showed how to generate random numbers in SAS by using the RAND function in the DATA step or by using the RANDGEN subroutine in SAS/IML software. These functions generate a stream of random numbers. (In statistics, the random numbers are usually a sample from a distribution such as
One of the highly visible changes in SAS 9.3 is the fact that the old LISTING destination is no longer the default destination for ODS output. Instead, the HTML destination is the default. One positive consequence of this is that ODS graphics and tables are interlaced in the output. Another
Exploring correlation between variables is an important part of exploratory data analysis. Before you start to model data, it is a good idea to visualize how variables related to one another. Zach Mayer, on his Modern Toolmaking blog, posted code that shows how to display and visualize correlations in R.
You can generate a set of random numbers in SAS that are uniformly distributed by using the RAND function in the DATA step or by using the RANDGEN subroutine in SAS/IML software. (These same functions also generate random numbers from other common distributions such as binomial and normal.) The syntax
NOTE: SAS stopped shipping the SAS/IML Studio interface in 2018. It is no longer supported, so this article is no longer relevant. When I write SAS/IML programs, I usually do my development in the SAS/IML Studio environment. Why? There are many reasons, but the one that I will discuss today
Some people search the Internet for a set of topics and then use the number of search results ("hits") for each topic to rank the relative popularity of the topics. At the 2011 Joint Statistical Meetings (JSM), I had the opportunity to attend several talks by statisticians from Google and
