Writing efficient SAS/IML programs is very important. One aspect to efficient SAS/IML programming is to avoid unnecessary DO loops. In my book, Statistical Programming with SAS/IML Software, I wrote (p. 80): One way to avoid writing unnecessary loops is to take full advantage of the subscript reduction operators for matrices.
In a previous blog post, I presented a short SAS/IML function module that implements the trapezoidal rule. The trapezoidal rule is a numerical integration scheme that gives the integral of a piecewise linear function that passes through a given set of points. This article demonstrates an application of using the
In a previous article I discussed the situation where you have a sequence of (x,y) points and you want to find the area under the curve that is defined by those points. I pointed out that usually you need to use statistical modeling before it makes sense to compute the
The other day I was asked, "Given a set of points, what is the area under the curve defined by those points?" As stated, the problem is not well defined. The problem is that "the curve defined by those points" doesn't have a precise meaning. However, after gathering more information,
Recently I had to compute the trace of a product of square matrices. That is, I had two large nxn matrices, A and B, and I needed to compute the quantity trace(A*B). Furthermore, I was going to compute this quantity thousands of times for various A and B as part
Did you know that you can display a list of all the SAS/IML variables (matrices) that are defined in the current session? The SHOW statement performs this useful task. For example, the following statements define three matrices: proc iml; fruit = {"apple", "banana", "pear"}; k = 1:3; x = j(1E5,
Many people know that the SGPLOT procedure in SAS 9.2 can create a large number of interesting graphs. Some people also know how to create a panel of graphs (all of the same type) by using the SGPANEL procedure. But did you know that you can also create a panel
This article shows how to randomly access data in a SAS data set by using the READ POINT statement in SAS/IML software. I have previously discussed how to use the READ NEXT and READ CURRENT statements to sequentially access each observation in a SAS data set from PROC IML. Reading
Andrew Ratcliffe posted a fine article titled "Inadequate Mends" in which he extols the benefits of including the name of a macro on the %MEND statement. That is, if you create a macro function named foo, he recommends that you include the name in two places: %macro foo(x); /** define
A fundamental operation in data analysis is finding data that satisfy some criterion. How many people are older than 85? What are the phone numbers of the voters who are registered Democrats? These questions are examples of locating data with certain properties or characteristics. The SAS DATA step has a
