SAS programmers use the SAS/IML language for many different tasks. One important task is computing an integral. Another is optimizing functions, such as maximizing a likelihood function to find parameters that best fit a set of data. Last week I saw an interesting problem that combines these two important tasks.
A colleague sent me an interesting question: What is the best way to abort a SAS/IML program? For example, you might want to abort a program if the data is singular or does not contain a sufficient number of observations or variables. As a first attempt would be to try
My last blog post described three ways to add a smoothing spline to a scatter plot in SAS. I ended the post with a cautionary note: From a statistical point of view, the smoothing spline is less than ideal because the smoothing parameter must be chosen manually by the user.
Like many SAS programmers, I use the Statistical Graphics (SG) procedures to graph my data in SAS. To me, the SGPLOT and SGRENDER procedures are powerful, easy to use, and produce fabulous ODS graphics. I was therefore surprised when a SAS customer told me that he continues to use the
My previous post described how to use the "missing response trick" to score a regression model. As I said in that article, there are other ways to score a regression model. This article describes using the SCORE procedure, a SCORE statement, the relatively new PLM procedure, and the CODE statement.
A fundamental operation in statistical data analysis is to fit a statistical regression model on one set of data and then evaluate the model on another set of data. The act of evaluating the model on the second set of data is called scoring. One of first "tricks" that I
Although I currently work as a statistician, my original training was in mathematics. In many mathematical fields there is a result that is so profound that it earns the name "The Fundamental Theorem of [Topic Area]." A fundamental theorem is a deep (often surprising) result that connects two or more
One of my favorite new features of SAS/IML 12.1 enables you to define functions that contain default values for parameters. This is extremely useful when you want to write a function that has optional arguments. Example: Centering a data vector It is simple to specify a SAS/IML module with a
Finding the root (or zero) of a function is an important computational task because it enables you to solve nonlinear equations. I have previously blogged about using Newton's method to find a root for a function of several variables. I have also blogged about how to use the bisection method
Last week I showed three ways to sample with replacement in SAS. You can use the SAMPLE function in SAS/IML 12.1 to sample from a finite set or you can use the DATA step or PROC SURVEYSELECT to extract a random sample from a SAS data set. Sampling without replacement
