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. 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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In my four years of blogging, the post that has generated the most comments is "How to handle negative values in log transformations." Many people have written to describe data that contain negative values and to ask for advice about how to log-transform the data. Today I describe a transformation […]Post a Comment
In my previous blog post, I showed how to use log axes on a scatter plot in SAS to better visualize data that range over several orders of magnitude. Because the data contained counts (some of which were zero), I used a custom transformation x → log10(x+1) to visualize the […]Post a Comment
If you are trying to visualize numerical data that range over several magnitudes, conventional wisdom says that a log transformation of the data can often result in a better visualization. This article shows several ways to create a scatter plot with logarithmic axes in SAS and discusses some of the […]Post a Comment
A few years ago I blogged about how to expand a data set by using a frequency variable. The DATA step in the article was simple, but the SAS/IML function was somewhat complicated and used a DO loop to expand the data. (Although a reader later showed how to avoid […]Post a Comment
Last week I showed how to use the SUBMIT and ENDSUBMIT statements in the SAS/IML language to call the SGPLOT procedure to create ODS graphs of data that are in SAS/IML vectors and matrices. I also showed how to create a SAS/IML module that hides the details and enables you […]Post a Comment
As you develop a program in the SAS/IML language, it is often useful to create graphs to visualize intermediate results. I do this all the time in my preferred development environment, which is SAS/IML Studio. In SAS/IML Studio, you can write a single statement to create a scatter plot, bar […]Post a Comment
A colleague asked me an interesting question: I have a journal article that includes sample quantiles for a variable. Given a new data value, I want to approximate its quantile. I also want to simulate data from the distribution of the published data. Is that possible? This situation is common. […]Post a Comment
A colleague sent me an interesting question: What is the best way to abort a SAS/IML program? For example, you might want to abort a program if the data is singular or does not contain a sufficient number of observations or variables. As a first attempt would be to try […]Post a Comment
My last blog post described three ways to add a smoothing spline to a scatter plot in SAS. I ended the post with a cautionary note: From a statistical point of view, the smoothing spline is less than ideal because the smoothing parameter must be chosen manually by the user. […]Post a Comment
In 2013 I published 110 blog posts. Some of these articles were more popular than others, often because they were linked to from a SAS newsletter such as the SAS Statistics and Operations Research News. In no particular order, here are some of my most popular posts from 2013, organized […]Post a Comment