The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
Today is my 500th blog post for The DO Loop. I decided to celebrate by doing what I always do: discuss a statistical problem and show how to solve it by writing a program in SAS. Two ways to parameterize the lognormal distribution I recently blogged about the relationship between
In many areas of statistics, it is convenient to be able to easily construct a uniform grid of points. You can use a grid of parameter values to visualize functions and to get a rough feel for how an objective function in an optimization problem depends on the parameters. And
In my book Simulating Data with SAS, I specify how to generate lognormal data with a shape and scale parameter. The method is simple: you use the RAND function to generate X ~ N(μ, σ), then compute Y = exp(X). The random variable Y is lognormally distributed with parameters μ
Sometimes you have data in SAS/IML vectors that you need to write to a SAS data set. By default, no formats are associated with the variables that you create from SAS/IML vectors. However, some variables (notably dates, times, and datetimes) should have formats associated with the data values. You can
A little-known but useful feature of SAS/IML 12.3 (which was released with SAS 9.4) is the ability to generate a vector of lowercase or uppercase letters by using the colon operator (:). Many SAS/IML programmers use the colon operator to generate a vector of sequential integers: proc iml; x =
Last week, as part of an article on how spammers generate comments for blogs, I showed how to generate random messages by using the CATX function in the DATA step. In that example, the strings were scalar quantities, but you can also concatenate vectors of strings in the SAS/IML language.