The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
Today is the birthday of Bernhard Riemann, a German mathematician who made fundamental contributions to the fields of geometry, analysis, and number theory. Riemann is definitely on my list of the greatest mathematicians of all time, and his conjecture about the distribution of prime numbers is one of the great
Missing values are a fact of life. Many statistical analyses, such as regression, exclude observations that contain missing values prior to forming matrix equations that are used in the analysis. This post shows how to find rows of a data matrix that contain missing values and how to remove those
Peter Flom reminded readers of his blog that you should always end a SAS procedure with a RUN statement. This is good rule. However, PROC IML is an exception to the rule. In PROC IML, the RUN statement is used to execute a built-in subroutine or a user-defined module. You
A frequently performed task in data analysis is identifying all the observations in a data set that satisfy certain conditions. For example, you might want to identify all of the female patients in your study or to identify all patients whose systolic blood pressure is greater than 140 mm Hg.
"How do I apply a format to a vector of values in IML? In the DATA step, I can just call the PUTN function.” This question came from a SAS customer that I met recently at a conference. My reply? Use the PUTN function, but send it a vector of
The R You Ready blog posed an interesting problem. Essentially, you have a vector that contains n(n+1)/2 elements, and you want to pack those elements into the upper left triangular portion of a matrix. For example, if your data are proc iml; /** vector v is given: ncol(v) = n(n+1)/2 for