Author

Rick Wicklin
RSS
Distinguished Researcher in Computational Statistics

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.

Rick Wicklin 6
Sample without replacement in SAS

Last week I showed three ways to sample with replacement in SAS. You can use the SAMPLE function in SAS/IML 12.1 to sample from a finite set or you can use the DATA step or PROC SURVEYSELECT to extract a random sample from a SAS data set. Sampling without replacement

Rick Wicklin 14
Sample with replacement in SAS

Randomly choosing a subset of elements is a fundamental operation in statistics and probability. Simple random sampling with replacement is used in bootstrap methods (where the technique is called resampling), permutation tests and simulation. Last week I showed how to use the SAMPLE function in SAS/IML software to sample with

Rick Wicklin 0
Say hello to SAS Analytics 13.1

Late last month, while many of us were sipping eggnog and decking halls with boughs of holly, SAS released the 13.1 version of its analytical products. Readers of Maura Stokes' newsletter, SAS Statistics and Operations Research News (Nov 2013), have already been alerted to new features in products such as

Learn SAS
Rick Wicklin 1
How to vectorize time series computations

Vector languages such as SAS/IML, MATLAB, and R are powerful because they enable you to use high-level matrix operations (matrix multiplication, dot products, etc) rather than loops that perform scalar operations. In general, vectorized programs are more efficient (and therefore run faster) than programs that contain loops. For an example

1 102 103 104 105 106 150