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.
A previous article about how to display missing values in SAS prompted a comment about special missing values in ODS tables in SAS. Did you know that statistical tables in SAS include special missing values to represent certain situations in statistical analyses? This article explains how to interpret four special
In statistical tables in SAS, a dot (.) represents a numerical missing value. Although a dot is the default symbol in SAS, other languages use other symbols. The R language prints the symbol NA, which stands for "not available." The MATLAB language uses NaN ("Not a Number"). In Python, many
Modern software for statistical graphics automatically handles many details and graph defaults, such as the range of the axes and the placement of tick marks. In the days of yore, these details required tedious manual calculations. Think about what is required to place ticks on a scatter plot. On the
In SAS, DATA step programmers use the IN operator to determine whether a value is contained in a set of target values. Did you know that there is a similar functionality in the SAS IML language? The ELEMENT function in the SAS IML language is similar to the IN operator
A previous article shows how to implement recursive formulas in SAS. The article points out that you can often avoid recursion by using an iterative algorithm, which is more efficient. An example is the Fibonacci sequence, which is usually defined recursively as F(n) = F(n-1) + F(n-2) for n
Many well-known distributions become more and more "normal looking" for large values of a parameter. Famously, the binomial distribution, Binom(p, N), can be approximated by a normal distribution when N (the sample size) is large. Similarly, the Poisson(λ) distribution is well approximated by the normal distribution when λ is large.
There are two programming tools that I rarely use: the SAS macro language and recursion. The SAS macro language is a tool that enables you to generate SAS statements. I rarely use the SAS macro language because the SAS IML language supports all the functionality required to write complex programs,
The SAS IML Language has a quirk with regards to functions that take no arguments. As discussed in the documentation, "modules with arguments are given a local symbol table." This is the usual behavior that programmers expect. However, the documentation goes on to state that "a module that has no
In SAS, the easiest way to draw random sampling from data is to use PROC SURVEYSELECT or the SAMPLE function in SAS IML software. I have previously written about how to implement four common sampling schemes by using PROC SURVEYSELECT and the SAMPLE function. The DATA step in SAS is
This article shows how to simulate data from a Poisson regression model, including how to account for an offset variable. If you are not familiar with how to run a Poisson regression in SAS, see the article "Poisson regression in SAS." A Poisson regression model is a specific type of
