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.
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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
A SAS programmer wanted to plot the normal distribution and highlight the area under curve that corresponds to the tails of the distribution. For example, the following plot shows the lower decile shaded in blue and the upper decile shaded in red. An easy way to do this in SAS [...]Post a Comment
As my colleague Margaret Crevar recently wrote, it is useful to know how long SAS programs take to run. Margaret and others have written about how to use the SAS FULLSTIMER option to monitor the performance of the SAS system. In fact, SAS distributes a macro that enables you to [...]Post a Comment
When I am computing with SAS/IML matrices and vectors, I often want to label the columns or rows so that I can better understand the data. The labels are called headers, and the COLNAME= and ROWNAME= options in the SAS/IML PRINT statement enable you to add headers for columns and [...]Post a Comment
One of the fundamental principles of computer programming is to break a task into smaller subtasks and to modularize the program by encapsulating each subtask into its own function. I have written many blog posts over the years about how to define and use functions in the SAS/IML language. I [...]Post a Comment
A SAS programmer asked for a list of SAS/IML functions that operate on the columns of an n x p matrix and return a 1 x p row vector of results. The functions that behave this way tend to compute univariate descriptive statistics such as the mean, median, standard deviation, and quantiles. The following [...]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
A common task in data analysis is to locate observations that satisfy multiple criteria. For example, you might want to locate all zip codes in certain counties within specified states. The SAS DATA step contains the powerful WHERE statement, which enables you to extract a subset of data that satisfy [...]Post a Comment
Did you know that if you have set multiple titles in SAS, that there is an easy way to remove them? For example, suppose that you've written the following statements, which call the TITLE statement to set three titles: title "A Great Big Papa Title"; title2 "A Medium-sized Mama Title"; [...]Post a Comment