The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
O Christmas tree, O Christmas tree, How lovely are your branches! SAS programmers have a long history of creating yuletide-themed graphics. Christmas trees are a popular image because of their simplicity. I admit that I have indulged more than once in this holiday tradition: An old-school ASCII art image A
While researching the topic of Latin hypercube sampling (LHS), I read an article by Emily Gao (2019) that shows how to use PROC IML in SAS to perform the algorithm. It is possible to simplify Gao's implementation of Latin hypercube sampling in SAS while also making the computation more efficient.
Decades ago, it was a challenge to generate (pseudo-) random numbers that had good statistical properties. The proliferation of desktop computers in the 1980s and '90s led to many advances in computational mathematics, including better ways to generate pseudorandom variates from a wide range of probability distributions. (For brevity, I
The article "Order two-dimensional vectors by using angles" shows how to re-order a set of 2-D vectors by their angles. Because angles are on a circle, which has no beginning and no end, you must specify which vector will appear first in the list. The previous article finds the largest
Order matters. The order of variables in tables and rows of a correlation matrix can make a big difference in how easy it is to observed correlations between variables or groups of variables. There are many ways to order the variables, but this article shows how to display the variables
In a correlation analysis, it is common to consider the correlations between all pairs of numerical variables. That is, if there are k numerical variables, most people examine the complete k x k matrix of correlations. This matrix is symmetric and has 1s on the diagonal, so more than half of the