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

## Tag: **Statistical Programming**

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

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

Sampling with replacement is a useful technique for simulations and for resampling from data. Over at the SAS/IML Discussion Forum, there was a recent question about how to use SAS/IML software to sample with replacement from a set of events. I have previously blogged about efficient sampling, but this topic

The SAS/IML language provides the QUAD function for evaluating one-dimensional integrals. You can also use the QUAD function to compute a double integral as an iterated integral. A One-Dimensional Integration Suppose you want to evaluate the following integral: To evaluate this integral in the SAS/IML language: Define a function module

I was recently asked how to create a tridiagonal matrix in SAS/IML software. For example, how can you easily specify the following symmetric tridiagonal matrix without typing all of the zeros? proc iml; m = {1 6 0 0 0, 6 2 7 0 0, 0 7 3 8 0,

In a previous post, I discussed how to use the LOC function to eliminate loops over observations. Dale McLerran chimed in to remind me that another way to improve efficiency is to use subscript reduction operators. I ended my previous post by issuing a challenge: can you write an efficient

Have you ever been stuck while trying to solve a scrambled-word puzzle? You stare and stare at the letters, but no word reveals itself? You are stumped. Stymied. I hope you didn't get stumped on the word puzzle I posted as an anniversary present for my wife. She breezed through

In a previous post, I discussed how to generate random permutations of N elements. But what if you want to systematically iterate through a list of ALL permutations of N elements? In the SAS DATA step you can use the ALLPERM subroutine in the SAS DATA step. For example, the