# The DO Loop

Statistical programming in SAS with an emphasis on SAS/IML programsOften, the first step of a SAS/IML program is to use the USE, READ, and CLOSE statements to read data from a SAS data set into a vector or matrix. There are several ways to read data: Read variables into vectors of the same name. Read one or more variables

In a previous blog post about hurricanes, I created a histogram of the occurrence of tropical cyclones in the Atlantic basin during the years 1988–2003. That histogram shows that the peak of hurricane activity occurs in the second week of September, but also that a majority of tropical storms occur

This morning I read an interesting post about the design of the new Twitter Web page. The post included some R code to generate the ratio between adjacent terms in the Fibonacci seqence. The ratio converges to the "Golden Ratio": 1.61803399.... I'm sure that many R gurus will post simpler

The SAS/IML language is a vector language, so statements that operate on a few long vectors run much faster than equivalent statements that involve many scalar quantities. For example, in a previous post, I asserted that the LOC function is much faster than writing a loop, for finding observations that

The Junk Chart blog discusses a potential problem that can arise in grouped bar charts when the two groups have vastly different ranges. One possible solution (which is discussed at the Junk Chart sister blog, Numbers Rule Your World) is to present the data back-back in what is sometimes called

The SAS/IML run-time library contains hundreds of functions and subroutines that you can call to perform statistical analysis. There are also many functions in Base SAS software that you can call from SAS/IML programs. However, one day you might need to compute some quantity for which there is no prewritten