It is common to want to extract the lower or upper triangular elements of a matrix. For example, if you have a correlation matrix, the lower triangular elements are the nontrivial correlations between variables in your data. As I've written before, you can use the VECH function to extract the
Sometimes a small option can make a big difference. Last week I thought to myself, "I wish there were an option that prevents variable labels from appearing in a table or graph." Well, it turns out that there is! I was using PROC MEANS to display some summary statistics, and
I've seen analyses of Fisher's iris data so often that sometimes I feel like I can smell the flowers' scent. However, yesterday I stumbled upon an analysis that I hadn't seen before. The typical analysis is shown in the documentation for the CANDISC procedure in the SAS/STAT documentation. A (canonical)
A comment to last week's article on "How to get data values out of ODS graphics" indicated that the technique would be useful for changing the title on an ODS graph "without messing around with GTL." You can certainly use the technique for that purpose, but if you want to
Many SAS procedures can produce ODS statistical graphics as naturally as they produce tables. Did you know that it is possible to obtain the numbers underlying an ODS statistical graph? This post shows how. Suppose that a SAS procedure creates a graph that displays a curve and that you want
I received the following question: In the DATA step I always use the ** operator to raise a values to a power, like this: x**2. But on your blog I you use the ## operator to raise values to a power in SAS/IML programs. Does SAS/IML not support the **
Last week I wrote an article in which I pointed out that many SAS programmers write a simulation in SAS by writing a macro loop. This approach is extremely inefficient, so I presented a more efficient technique. Not only is the macro loop approach slow, but there are other undesirable
Over the past few years, and especially since I posted my article on eight tips to make your simulation run faster, I have received many emails (often with attached SAS programs) from SAS users who ask for advice about how to speed up their simulation code. For this reason, I
I have blogged about three different SAS/IML techniques that iterate over categories and process the observations in each category. The three techniques are as follows: Use a WHERE clause on the READ statement to read only the observations in the ith category. This is described in the article "BY-group processing
When you are working with probability distributions (normal, Poisson, exponential, and so forth), there are four essential functions that a statistical programmer needs. As I've written before, for common univariate distributions, SAS provides the following functions: the PDF function, which returns the probability density at a given point the CDF
