The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
Simulation studies require both randomness and reproducibility, two qualities that are sometimes at odds with each other. A Monte Carlo simulation might need to generate millions of random samples, where each sample contains dozens of continuous variables and many thousands of observations. In simulation studies, the researcher wants each sample
Order matters. When you create a graph that has a categorical axis (such as a bar chart), it is important to consider the order in which the categories appear. Most software defaults to alphabetical order, which typically gives no insight into how the categories relate to each other. Alphabetical order
Some say that opposites attract. Others say that birds of a feather flock together. Which is it? Phillip N. Cohen, a professor of sociology at the University of Maryland, recently posted an interesting visualization that indicates that married couples who are college graduates tend to be birds of a feather.
SAS programmers on SAS discussion forums sometimes ask how to run thousands of regressions of the form Y = B0 + B1*X_i, where i=1,2,.... A similar question asks how to solve thousands of regressions of the form Y_i = B0 + B1*X for thousands of response variables. I have previously
You've probably heard about the "80-20 Rule," which describes many natural and manmade phenomena. This rule is sometimes called the "Pareto Principle" because it was discovered by Vilfredo Pareto (1848–1923) who used it to describe the unequal distribution of wealth. Specifically, in his study, 80% of the wealth was held
The sweep operator performs elementary row operations on a system of linear equations. The sweep operator enables you to build regression models by "sweeping in" or "sweeping out" particular rows of the X`X matrix. As you do so, the estimates for the regression coefficients, the error sum of squares, and