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3 reasons to learn more about JSL

With the publication of JSL Companion: Applications of the JMP Scripting Language, by Theresa Utlaut, Georgia Morgan, and Kevin Anderson, novice scripters now have a resource that helps them go beyond the basics of the JMP Scripting Language (JSL). Why JSL? The authors have the answers: 1.  Easy to start

Rick Wicklin 0
ANY versus ALL: Testing the elements of a vector

The fundamental units in the SAS/IML language are matrices and vectors. Consequently, you might wonder about conditional expression such as if v>0 then.... What does this expression mean when v contains more than a single element? Evaluating vector expressions When you test a vector for some condition, expressions like v>0

Analytics
Vincent Talucci 0
Promises, (over)promises

As public safety officials leaf through their favorite criminal justice periodical they are greeted with pages and pages of analytics advertisements. These ads are laden with promises of robust and scalable solutions, improved efficiencies and, yes, the promise of prediction. While reading the advertisements, the mental conversation may go something

SAS Events
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Top 3 tips for advanced SAS programmers

Art Carpenter’s newest book, Carpenter’s Guide to Innovative SAS Techniques, offers advanced SAS programmers an all-in-one programming reference that includes advanced topics not easily found outside the depths of SAS documentation or more advanced training classes. No matter how you approach the use of SAS software, the techniques provided in

Rick Wicklin 0
Row vectors versus column vectors

The SAS/IML language supports both row vectors and column vectors. This is useful for performing linear algebra, but it can cause headaches when you are writing a SAS/IML module. I want my modules to be able to handle both row vectors and column vectors. I don't want the user to

Data Visualization
Sanjay Matange 0
Graphs with class

When the data is classified by multiple class variables, you can certainly create graphs using BY variables.  This results in separate graphs, one for each level of the BY variable crossings.  Each graph is scaled by its own data subset, and comparisons across BY levels is harder. When comparisons need to be

Rick Wicklin 0
Linear interpolation in SAS/IML

A recent discussion on the SAS-L discussion forum concerned how to implement linear interpolation in SAS. Some people suggested using PROC EXPAND in SAS/ETS software, whereas others proposed a DATA step solution. For me, the SAS/IML language provides a natural programming environment to implement an interpolation scheme. It also provides

Mike Gilliland 0
More research from Harvard Business Review

There is something that 90% of us admit to doing, and the other 10% will lie about. That, of course, is Googling yourself. As an avid follower of myself, and everything I do, I look forward to a weekly Google Alert that tells me all about what I've been up to.

Chris Hemedinger 0
Making up for lost time (UTC vs. DST)

Did you oversleep this morning? If you live in the United States of America, Monday morning seems to have arrived just a bit earlier, accompanied by a bit more "dark" than usual. That's because as good time-fearing citizens, we have all set our clocks ahead by one hour so as

Rick Wicklin 0
Compute sample quantiles by using the QNTL call

SAS provides several ways to compute sample quantiles of data. The UNIVARIATE procedure can compute quantiles (also called percentiles), but you can also compute them in the SAS/IML language. Prior to SAS/IML 9.22 (released in 2010) statistical programmers could call a SAS/IML module that computes sample quantiles. With the release

Rick Wicklin 0
Quantiles of discrete distributions

I work with continuous distributions more often than with discrete distributions. Consequently, I am used to thinking of the quantile function as being an inverse cumulative distribution function (CDF). (These functions are described in my article, "Four essential functions for statistical programmers.") For discrete distributions, they are not. To quote

Chris Hemedinger 0
Be a code poet laureate

The next time you write a DATA step, try to express it in iambic pentameter.  Or instead of a SAS macro function, how about a SAS macro sonnet?  (Or, for the more base among you, a limerick?) That's the spirit behind the code {poems} project.  You write a poem in

Rick Wicklin 0
Testing data for multivariate normality

I've blogged several times about multivariate normality, including how to generate random values from a multivariate normal distribution. But given a set of multivariate data, how can you determine if it is likely to have come from a multivariate normal distribution? The answer, of course, is to run a goodness-of-fit

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