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.
At the beginning of 2011, I made four New Year's resolutions for my blog. As the year draws to a close, it's time to see how I did: Resolution: 100 blog posts in 2011: Completed. I blew by this goal by posting 165 articles. I recently compiled a list of
A few colleagues and I were exchanging short snippets of SAS code that create Christmas trees and other holiday items by using the SAS DATA step to arrange ASCII characters. For example, the following DATA step (contributed by Udo Sglavo) creates a Christmas tree with ornaments and lights: data _null_;
Since this is a blog about statistical programming and analysis, I am always looking for data to analyze. As 2011 ends, I look back on the 165 blog entries that I published since 01JAN2011. This article presents the 10 most popular posts, as determined by the number of people who
The SAS Output Delivery System (ODS) enables you to manage and customize tables (and graphics!) that are created by SAS procedures. I like to use the ODS SELECT statement to display only part of the output of a SAS procedure. For example, the UNIVARIATE procedure produces five tables by default,
Some SAS products such as SAS/IML Studio (which is included FREE as part of SAS/IML software) have interactive graphics. This makes it easy to interrogate a graph to determine values of "hidden" variables that might not appear in the graph. For example, in a scatter plot in SAS/IML Studio, you
Yesterday, December 7, 1941, a date which will live in infamy... - Franklin D. Roosevelt Today is the 70th anniversary of the Japanese attack on Pearl Harbor. The very next day, America declared war. During a visit to the Smithsonian National Museum of American History, I discovered the results of
In simulation studies, the response variable is often a binary (or Bernoulli) variable. Often 1 is used to indicate "success" (or the occurrence of an event) whereas 0 indicates "failure" (or the absence of an event). For example, the following SAS/IML statements define a vector x of zeros and ones:
Recently the "SAS Sample of the Day" was a Knowledge Base article with an impressively long title: Sample 42165: Using a stored process to eliminate duplicate values caused by multiple group memberships when creating a group-based, identity-driven filter in SAS® Information Map Studio "Wow," I thought. "This is the longest
The other day someone posted the following question to the SAS-L discussion list: Is there a SAS PROC out there that takes a multi-category discrete variable with character categories and converts it to a single numeric coded variable (not a set of dummy variables) with the character categories assigned as
I got an email asking the following question: In the following program, I don't know how many variables are in the data set A. However, I do know that the variable names are X1–Xk for some value of k. How can I read them all into a SAS/IML matrix when
