Rick Wicklin
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Research Statistician Developer

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. His areas of expertise include computational statistics, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS. Follow @RickWicklin on Twitter.

Recent Posts

On the number of permutations supported in SAS software

There's "big," and then there is "factorial big." If you have k items, the number of permutations is "k factorial," which is written as k!. ... Read More

Vectors that have a fractional number of elements

The title of this article makes no sense. How can the number of elements (in fact, the number of anything!) not be a whole number? ... Read More

Finding observations that match a target value

Imagine that you have one million rows of numerical data and you want to determine if a particular "target" value occurs. How might you find ... Read More

How to pass parameters to a SAS program

This article show how to run a SAS program in batch mode and send parameters into the program by specifying the parameters when you run ... Read More

Analyzing the first 10 million digits of pi: Randomness within structure

Saturday, March 14, 2015, is Pi Day, and this year is a super-special Pi Day! This is your once-in-a-lifetime chance to celebrate the first 10 ... Read More

Matrix multiplication with missing values in SAS

Sometimes I get contacted by SAS/IML programmers who discover that the SAS/IML language does not provide built-in support for multiplication of matrices that have missing ... Read More

Writing data in chunks: Does the chunk size matter?

I often blog about the usefulness of vectorization in the SAS/IML language. A one-sentence summary of vectorization is "execute a small number of statements that ... Read More

Create a custom PDF and CDF in SAS

In my previous post, I showed how to approximate a cumulative density function (CDF) by evaluating only the probability density function. The technique uses the ... Read More

An easy way to approximate a cumulative distribution function

Evaluating a cumulative distribution function (CDF) can be an expensive operation. Each time you evaluate the CDF for a continuous probability distribution, the software has ... Read More

Avoid loops, avoid the APPLY function, vectorize!

Last week I received a message from SAS Technical Support saying that a customer's IML program was running slowly. Could I look at it to ... Read More