About this blog
Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. This blog focuses on statistical programming. It discusses statistical and computational algorithms, statistical graphics, simulation, efficiency, and data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
Follow @RickWicklin on Twitter.
Tags9.3 9.4 9.22 12.1 12.3 13.1 13.2 14.1 Bootstrap and Resampling Ciphers Conferences Data Analysis Efficiency File Exchange Getting Started GTL Heat maps History IMLPlus Just for Fun Math Matrix Computations Numerical Analysis Optimization R Reading and Writing Data SAS/IML Studio SAS Global Forum SAS Programming Simulation Statistical Graphics Statistical Programming Statistical Thinking Strings Tips and Techniques vectorization Video
Subscribe to this blog
Statistical programmers often need to evaluate complicated expressions that contain square roots, logarithms, and other functions whose domain is restricted. Similarly, you might need to evaluate a rational expression in which the denominator of the expression can be zero. In these cases, it is important to avoid evaluating a function […]Post a Comment
Every year near Halloween I write a trick-and-treat article in which I demonstrate a simple programming trick that is a real treat to use. This year's trick features two of my favorite functions, the CUSUM function and the LAG function. By using these function, you can compute the rows of […]Post a Comment
I've previously written about how to generate a sequence of evenly spaced points in an interval. Evenly spaced data is useful for scoring a regression model on an interval. In the previous articles the endpoints of the interval were hard-coded. However, it is common to want to evaluate a function […]Post a Comment
Statistical programmers often have to use the results from one SAS procedure as the input to another SAS procedure. Because ODS enables you to you to create a SAS data set from any ODS table or graph, it is easy to obtain a data set that contains the value of […]Post a Comment
The title of this blog post might seem strange, but I occasionally need to compute the number of digits in a number, usually because I am trying to stuff an integer value into a string. Each time, I have to derive the formula from scratch, so I am writing this […]Post a Comment
One of my presentations at SAS Global Forum 2015 was titled "Ten Tips for Simulating Data with SAS". The paper was published in the conference proceedings several months ago, but I recently recorded a short video that gives an overview of the 10 tips: If your browser does not support […]Post a Comment
When using SAS to format a number as a percentage, there is a little trick that you need to remember: the width of the formatted value must include room for the decimal point, the percent sign, and the possibility of two parentheses that indicate negative values. The field width must […]Post a Comment
Base SAS contains many functions for processing strings, and you can call these functions from within a SAS/IML program. However, sometimes a SAS/IML programmer needs to process a vector of strings. No problem! You can call most Base SAS functions with a vector of parameters. I have previously written about […]Post a Comment
I previously wrote about the best way to suppress output from SAS procedures. Suppressing output is necessary in simulation and bootstrap analyses, and it is useful in other contexts as well. In my previous article, I wrote, "many programmers use ODS _ALL_ CLOSE as a way to suppress output, but […]Post a Comment
SAS procedures can produce a lot of output, but you don't always want to see it all. In simulation and bootstrap studies, you might analyze 10,000 samples or resamples. Usually you are not interested in seeing the results of each analysis displayed on your computer screen. Instead, you want to […]Post a Comment