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Rick Wicklin 0
The trapezoidal rule of integration

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

Rick Wicklin 0
Listing SAS/IML variables

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,

Rick Wicklin 0
Inadequate finishes

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

Rick Wicklin 0
Finding data that satisfy a criterion

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

Rick Wicklin 0
Calling R from SAS/IML software

For years I've been making presentations about SAS/IML software at conferences. Since 2008, I've always mentioned to SAS customers that they can call R from within SAS/IML software. (This feature was introduced in SAS/IML Studio 3.2 and was added to the IML procedure in SAS/IML 9.22.) I also included a

Rick Wicklin 0
The COALESCE function: PROC SQL compared with PROC IML

When Charlie H. posted an interesting article titled "Top 10 most powerful functions for PROC SQL," there was one item on his list that was unfamiliar: the COALESCE function. (Edit: Charlie's blog no longer exists. The article used to be available at http://www.sasanalysis.com/2011/01/top-10-most-powerful-functions-for-proc.html) Ever since I posted my first response,

Rick Wicklin 0
Where do major airlines fly?

Last week the Flowing Data blog published an excellent visualization of the flight patterns of major US airlines. On Friday, I sent the link to Robert Allison, my partner in the 2009 ASA Data Expo, which explored airline data. Robert had written a SAS program for the Expo that plots

Rick Wicklin 0
How to numerically integrate a function in SAS

This blog post shows how to numerically integrate a one-dimensional function by using the QUAD subroutine in SAS/IML software. The name "quad" is short for quadrature, which means numerical integration. You can use the QUAD subroutine to numerically find the definite integral of a function on a finite, semi-infinite, or

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JMP Essentials book wins international award

Congratulations to Curt Hinrichs and Chuck Boiler! Their book, JMP Essentials: An Illustrated Step-by-Step Guide for New Users, has won an Award of Distinguished Technical Communication in this year’s International Summit Awards presented by the Society for Technical Communication. The award goes to a project that “applies the principles of

Chris Hemedinger 0
I'm beta-testing 9.3. Buy me a drink?

Greg Nelson and Neil Howard presented a lunchtime keynote talk at SAS Global Forum, and they produced this video, "Revenge of the Semi-Colon People", to go along with it. The video features many people from the SAS community, including customers and SAS employees. Watch it and see if you know

Rick Wicklin 0
Variable transformations

One of the advantages of programming in the SAS/IML language is its ability to transform data vectors with a single statement. For example, in data analysis, the log and square-root functions are often used to transform data so that the transformed data have approximate normality. The following SAS/IML statements create

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