# 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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New Year's resolutions for my blog

It's a New Year and I'm ready to make some resolutions. Last year I launched this blog with my Hello, World post in which I said: In this blog I intend to discuss, describe, and disseminate ideas related to statistical programming with the SAS/IML language.... I will present tips and

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Automating the Great Christmas Gift Exchange

In many families, siblings draw names so that each family member and spouse gives and receives exactly one present. This year there was a little bit of controversy when a family member noticed that once again she was assigned to give presents to me. This post includes my response to

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Is the index to my book abnormally long?

When I finished writing my book, Statistical Programming with SAS/IML Software, I was elated. However, one small task still remained. I had to write the index. How Long Should an Index Be? My editor told me that SAS Press would send the manuscript to a professional editor who would index

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The module that vanished

Recently, I needed to detect whether a matrix consists entirely of missing values. I wrote the following module: proc iml; /** Module to detect whether all elements of a matrix are missing values. Works for both numeric and character matrices. Version 1 (not optimal) **/ start isMissing(x); if type(x)='C' then

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How to find and fix programming errors

There are three kinds of programming errors: parse-time errors, run-time errors, and logical errors. It doesn't matter what language you are using (SAS/IML, MATLAB, R, C/C++, Java,....), these errors creep up everywhere. Two of these errors cause a program to report an error, whereas the third is more insidious because

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Converting between correlation and covariance matrices

Both covariance matrices and correlation matrices are used frequently in multivariate statistics. You can easily compute covariance and correlation matrices from data by using SAS software. However, sometimes you are given a covariance matrix, but your numerical technique requires a correlation matrix. Other times you are given a correlation matrix,

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Computing covariance and correlation matrices

Sample covariance matrices and correlation matrices are used frequently in multivariate statistics. This post shows how to compute these matrices in SAS and use them in a SAS/IML program. There are two ways to compute these matrices: Compute the covariance and correlation with PROC CORR and read the results into