The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
A colleague posted some data on his internal SAS blog about key trends in the US Mobile phone industry, as reported by comScore. He graciously shared the data so that I could create a graph that visualizes the trends. The plot visualizes trends in the data: the Android phone is
When your data are in rows, but you need them in columns, use the matrix transpose function or operator. The same advice applies to data in columns that you want to be in rows. For example, the vectors created by the DO function and the index creation operator are row
A colleague related the following story: He was taking notes at a meeting that was attended by a fairly large group of people (about 20). As each person made a comment or presented information, he recorded the two-letter initials of the person who spoke. After the meeting was over, he
SAS/IML software is often used for sampling and simulation studies. For simulating data from univariate distributions, the RANDSEED and RANDGEN subroutines suffice to sample from a wide range of distributions. (I use the terms "sampling from a distribution" and "simulating data from a distribution" interchangeably.) For multivariate simulations, the IMLMLIB
It is often useful to create a vector with elements that follow an arithmetic sequence. For example, {1, 2, 3, 4} and {10, 30, 50, 70} are vectors with evenly spaced values. This post describes several ways to create vectors such as these. The SAS/IML language has two ways to
Computing probabilities can be tricky. And if you are a statistician and you get them wrong, you feel pretty foolish. That's why I like to run a quick simulation just to make sure that the numbers that I think are correct are, in fact, correct. My last post of 2010