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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The balanced bootstrap in SAS

I have previously blogged about ways to perform balanced bootstrap resampling in SAS. I recently learned about an easier way: Since SAS/STAT 14.2 (SAS 9.4M4), the SURVEYSELECT procedure has supported balanced bootstrap sampling. This article reviews balanced bootstrap sampling and shows how to use the METHOD=BALBOOT option in PROC SURVEYSELECT

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The McNemar test in SAS

What is McNemar's test? How do you run the McNemar test in SAS? Why might other statistical software report a value for McNemar's test that is different from the SAS value? SAS supports an exact version of the McNemar test, but when should you use it? This article answers these

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Pascal matrices and inverses

Some matrices are so special that they have names. The identity matrix is the most famous, but many are named after a researcher who studied them such as the Hadamard, Hilbert, Sylvester, Toeplitz, and Vandermonde matrices. This article is about the Pascal matrix, which is formed by using elements from

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Finite-difference derivatives of vector-valued functions

I previously showed how to use SAS to compute finite-difference derivatives for smooth scalar-valued functions of several variables. You can use the NLPFDD subroutine in SAS/IML software to approximate the gradient vector (first derivatives) and the Hessian matrix (second derivatives). The computation uses finite-difference derivatives to approximate the derivatives. The

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Finite-difference derivatives in SAS

Many applications in mathematics and statistics require the numerical computation of the derivatives of smooth multivariate functions. For simple algebraic and trigonometric functions, you often can write down expressions for the first and second partial derivatives. However, for complicated functions, the formulas can get unwieldy (and some applications do not

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Passing-Bablok regression in SAS

This article implements Passing-Bablok regression in SAS. Passing-Bablok regression is a one-variable regression technique that is used to compare measurements from different instruments or medical devices. The measurements of the two variables (X and Y) are both measured with errors. Consequently, you cannot use ordinary linear regression, which assumes that

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