About this blog
Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. His areas of expertise include computational statistics, statistical graphics, statistical simulation, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
Follow @RickWicklin on Twitter.
Subscribe to this blog
Tags9.3 9.4 9.22 12.1 12.3 13.1 13.2 Bootstrap and Resampling Ciphers Conferences Data Analysis Efficiency File Exchange Getting Started GTL Heat maps History IMLPlus Just for Fun Matrix Computations Numerical Analysis Optimization R Reading and Writing Data Sampling and Simulation SAS/IML Studio SAS Programming Statistical Graphics Statistical Programming Statistical Thinking Strings Tips and Techniques vectorization Video
Today is my 500th blog post for The DO Loop. I decided to celebrate by doing what I always do: discuss a statistical problem and show how to solve it by writing a program in SAS. Two ways to parameterize the lognormal distribution I recently blogged about the relationship between […]Post a Comment
SAS has supported calling R from the SAS/IML language since 2009. The interface to R is part of the SAS/IML language. However, there have been so many versions of SAS and R since 2009, that it is hard to remember which SAS release supports which versions of R. The following […]Post a Comment
Last week I presented two talks at the University of Wisconsin at Milwaukee, which has established a new Graduate Certificate in Applied Data Analysis Using SAS. While in Milwaukee, I ran into an old friend: the ODS LISTING destination. One of my presentations was a hands-on workshop titled Getting Started […]Post a Comment
I am pleased to announce that the documentation for the IMLPlus language is now available online. Previously, this resource was available only from within the SAS/IML Studio application. This documentation can now be accessed by anyone, regardless of whether they have installed SAS/IML Studio. As I have described previously, IMLPlus […]Post a Comment
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 is the fact that the application is multithreaded and supports multiple programming workspaces. The advantages of multiple programming workspaces I am always […]Post a Comment
For years I've been making presentations about SAS/IML software at conferences. Since 2008, I've always mentioned to SAS customers that they can call R from within SAS/IML software. (This feature was introduced in SAS/IML Studio 3.2 and was added to the IML procedure in SAS/IML 9.22.) I also included a […]Post a Comment
I was inspired by Chris Hemedinger's blog posts about his daughter's science fair project. Explaining statistics to a pre-teenager can be a humbling experience. My 11-year-old son likes science. He recently set about trying to measure which of three projectile launchers is the most accurate. I think he wanted to […]Post a Comment
If you tell my wife that she's married to a statistical geek, she'll nod knowingly. She is used to hearing sweet words of affection such as You are more beautiful than Euler's identity. or My love for you is like the exponential function: increasing, unbounded, and transcendental. But those are […]Post a Comment
Last week I generated two kinds of random point patterns: one from the uniform distribution on a two-dimensional rectangle, the other by jittering a regular grid by a small amount. My show choir director liked the second method (jittering) better because of the way it looks on stage: there are […]Post a Comment
Computing probabilities can be tricky. And if you are a statistician and you get them wrong, you feel pretty foolish. That's why I like to run a quick simulation just to make sure that the numbers that I think are correct are, in fact, correct. My last post of 2010 […]Post a Comment