About this blog
Rick Wicklin, PhD, is a senior 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, statistical simulation, 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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Each year my siblings choose names for a Christmas gift exchange. It is not unusual for a sibling to pick her own name, whereupon the name is replaced into the hat and a new name is drawn. In fact, that “glitch” in the drawing process was a motivation for me [...]Post a Comment
For several years, there has been interest in calling R from SAS software, primarily because of the large number of special-purpose R packages. The ability to call R from SAS has been available in SAS/IML since 2009. Previous blog posts about R include a video on how to call R [...]Post a Comment
When I call R from within the SAS/IML language, I often pass parameters from SAS into R. This feature enables me to write general-purpose, reusable, modules that can analyze data from many different data sets. I’ve previously blogged about how to pass values to SAS procedures from PROC IML by [...]Post a Comment
Last week I described how to generate permutations in SAS. A related concept is the “combination.” In probability and statistics, a combination is a subset of k items chosen from a set that contains N items. Order does not matter, so although the ordered triplets (B, A, C) and (C, [...]Post a Comment
This is the last post in my recent series of articles on computing contours in SAS. Last month a SAS customer asked how to compute the contours of the bivariate normal cumulative distribution function (CDF). Answering that question in a single blog post would have resulted in a long article, [...]Post a Comment
I’ve written several articles that show how to generate permutations in SAS. In the SAS DATA step, you can use the ALLPEM subroutine to generate all permutations of a DATA step array that contain a small number (18 or fewer) elements. In addition, the PLAN procedure enables you to generate [...]Post a Comment
The truncated normal distribution TN(μ, σ, a, b) is the distribution of a normal random variable with mean μ and standard deviation σ that is truncated on the interval [a, b]. I previously blogged about how to implement the truncated normal distribution in SAS. A friend wanted to simulate data [...]Post a Comment
How do you count the number of unique rows in a matrix? The simplest algorithm is to sort the data and then iterate down the rows, comparing each row with the previous row. However, this algorithm has two shortcomings: it physically sorts the data (which means that the original locations [...]Post a Comment
Last week I showed how to use simulation to estimate the power of a statistical test. I used the two-sample t test to illustrate the technique. In my example, the difference between the means of two groups was 1.2, and the simulation estimated a probability of 0.72 that the t [...]Post a Comment
The power of a statistical test measures the test’s ability to detect a specific alternate hypothesis. For example, educational researchers might want to compare the mean scores of boys and girls on a standardized test. They plan to use the well-known two-sample t test. The null hypothesis is that the [...]Post a Comment