# Author

Distinguished Researcher in Computational Statistics

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, simulation, 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.

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Matrices, eigenvalues, Fibonacci, and the golden ratio

A previous post described a simple algorithm for generating Fibonacci numbers. It was noted that the ratio between adjacent terms in the Fibonacci sequence approaches the "Golden Ratio," 1.61803399.... This post explains why. In a discussion with my fellow blogger, David Smith, I made the comment "any two numbers (at

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Often, 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

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Using data to define hurricane season

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

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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

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Timing Performance: Looping versus LOC-ing

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

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Comparing cell phone use by age

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

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Extending IML - Defining a Function Module

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

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When is the peak of hurricane season?

Visualizing the distribution of data is a primary task of data analysis. With all the hurricane activity in the Atlantic this year, I’ve been thinking about ways to visualize the historical distribution of hurricane activity. USA Today on Friday, August 13, 2010, announced that "the heart of hurricane season is