The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
In a previous blog post, I described the rules for a tic-tac-toe scratch-off lottery game and showed that it is a bad idea to generate the game tickets by using a scheme that uses equal probabilities. Instead, cells that yield large cash awards must be assigned a small probability of
Because of this week's story about a geostatistician, Mohan Srivastava, who figured out how predict winning tickets in a scratch-off lottery, I've been thinking about scratch-off games. He discovered how to predict winners when he began to "wonder how they make these [games]." Each ticket has a set of "lucky
I enjoyed the Dataists' data-driven blog on the best numbers to choose in a Super Bowl betting pool. It reminded me of my recent investigation of which initials are most common. Because the Dataists' blog featured an R function that converts Arabic numerals into Roman numerals, the blog post also
The other day, someone asked me how to compute a matrix of pairwise differences for a vector of values. The person asking the question was using SQL to do the computation for 2,000 data points, and it was taking many hours to compute the pairwise differences. He asked if SAS/IML
On Friday, I posted an article about using spatial statistics to detect whether a pattern of points is truly random. That day, one of my colleagues asked me whether there are any practical applications of detecting spatial randomness or non-randomness. "Oh, sure," I replied, and rattled off a list of
When you pass a matrix as an parameter (argument) to a SAS/IML module, the SAS/IML language does not create a copy of the matrix. That approach, known as "calling by value," is inefficient. It is well-known that languages that implement call-by-value semantics suffer performance penalties. In the SAS/IML language, matrices