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Rick WicklinJuly 13, 2015 3

Compare the performance of algorithms in SAS

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

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Rick WicklinJune 29, 2015 1

An easy way to use numbers for column headers

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

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Rick WicklinJune 17, 2015 4

Everything you wanted to know about writing SAS/IML modules

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

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Rick WicklinJune 1, 2015 7

SAS/IML functions that operate on columns of a matrix

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

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Rick WicklinMay 28, 2015 7

Five reasons to use ODS EXCLUDE to suppress SAS output

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

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Rick WicklinMay 11, 2015 3

Finding observations that satisfy multiple conditions: The LOC-ELEMENT technique

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

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Rick WicklinMay 4, 2015 5

An easy way to clear your SAS titles

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";

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Rick WicklinApril 22, 2015 4

Sum a series in SAS

A customer asked: How do we go about summing a finite series in SAS? For example, I want to compute for various integers n ≥ 3. I want to output two columns, one for the natural numbers and one for the summation of the series. Summations arise often in statistical

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Rick WicklinMarch 9, 2015 2

Writing data in chunks: Does the chunk size matter?

I often blog about the usefulness of vectorization in the SAS/IML language. A one-sentence summary of vectorization is "execute a small number of statements that each analyze a lot of data." In general, for matrix languages (SAS/IML, MATLAB, R, ...) vectorization is more efficient than the alternative, which is to

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Rick WicklinMarch 2, 2015 1

Avoid loops, avoid the APPLY function, vectorize!

Last week I received a message from SAS Technical Support saying that a customer's IML program was running slowly. Could I look at it to see whether it could be improved? What I discovered is a good reminder about the importance of vectorizing user-defined modules. The program in this blog

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