The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
In a previous post, I discussed computing regression coefficients in different polynomial bases and showed how the coefficients change when you change the basis functions. In particular, I showed how to convert the coefficients computed in one basis to coefficients computed with respect to a different basis. It turns out
I am pleased to announce that the fine folks at SAS Press have made Chapter 2 of my book, Statistical Programming with SAS/IML Software available as a free PDF document. The chapter is titled "Getting Started with the SAS/IML Matrix Programming Language," and it features More than 60 fully functional
The other day I was at the grocery store buying a week's worth of groceries. When the cashier, Kurt (not his real name), totaled my bill, he announced, "That'll be ninety-six dollars, even." "Even?" I asked incredulously. "You mean no cents?" "Yup," he replied. "It happens." "Wow," I said, with
Chris started a tradition for SAS Press authors to post a photo of themselves with their new book. Thanks to everyone who helped with the production of Statistical Programming with SAS/IML Software.
Suppose that you compute the coefficients of a polynomial regression by using a certain set of polynomial effects and that I compute coefficients for a different set of polynomial effects. Can I use my coefficients to find your coefficients? The answer is yes, and this article explains how. Standard Polynomial
I just got back from a great conference in San Diego at the 2010 meeting of the Western Users of SAS Software (WUSS) where I gave several presentations on PROC IML and SAS/IML Studio. If you didn't make it to San Diego, you can still read my 2010 paper on
