Author

Rick Wicklin
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Distinguished Researcher in Computational Statistics

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. 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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Create a contour plot in SAS

When I need to graph a function of two variables, I often choose to use a contour plot. A surface plot is probably easier for many people to understand, but it has several disadvantages when compared to a contour plot. For example, the following statements in SAS/IML Studio displays a

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A statistically beautiful Father's Day

To celebrate special occasions like Father's Day, I like to relax with a cup of coffee and read the newspaper. When I looked at the weather page, I was astonished by the seeming uniformity of temperatures across the contiguous US. The weather map in my newspaper was almost entirely yellow

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The curious case of random eigenvalues

I've been a fan of statistical simulation and other kinds of computer experimentation for many years. For me, simulation is a good way to understand how the world of statistics works, and to formulate and test conjectures. Last week, while investigating the efficiency of the power method for finding dominant

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BY-group processing in SAS/IML

Because the SAS/IML language is a general purpose programming language, it doesn't have a BY statement like most other SAS procedures (such as PROC REG). However, there are several ways to loop over categorical variables and perform an analysis on the observations in each category. One way is to use

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The Poissonness plot: A goodness-of-fit diagnostic

Last week I discussed how to fit a Poisson distribution to data. The technique, which involves using the GENMOD procedure, produces a table of some goodness-of-fit statistics, but I find it useful to also produce a graph that indicates the goodness of fit. For continuous distributions, the quantile-quantile (Q-Q) plot

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