Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
At the beginning of my book Statistical Programming with SAS/IML Software I give the following programming tip (p. 25): Do not confuse an empty matrix with a matrix that contains missing values or with a zero matrix. An empty matrix has no rows and no columns. A matrix that contains
Data simulation is a fundamental technique in statistical programming and research. My book Simulating Data with SAS is an accessible how-to book that describes the most useful algorithms and the best programming techniques for efficient data simulation in SAS. Here are five lessons you can learn by reading it: Learn strategies
A common task in SAS/IML programming is finding elements of a SAS/IML matrix that satisfy a logical expression. For example, you might need to know which matrix elements are missing, are negative, or are divisible by 2. In the DATA step, you can use the WHERE clause to subset data.
