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Rick WicklinAugust 4, 2025 4

Exponential overflow, underflow, and the sum-of-exponentials trick

Many common probability distributions contain terms that increase or decrease quickly, such as the exponential function and factorials. The numerical evaluation of these quantities can result in numerical overflow (or underflow). This is why we often work on the logarithmic scale: on the log-scale, the numerical computations for equations such

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Data Visualization | Learn SAS | Programming Tips

Rick WicklinJuly 28, 2025 0

How to position tick marks for months when you graph weekly data

Suppose you measure data weekly. According to the ISO standard, weeks are measured in the range 1-53, where most years have 52 weeks, but occasionally there is a "leap week." (The WEEK function in SAS implements the ISO standard to find the week-of-the-year for any date.) The heat map to

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Learn SAS | Programming Tips

Rick WicklinJuly 21, 2025 4

Strengthen your SAS skills with the WEEK function

Dating can be a challenge. No, I'm not talking about the process of finding a soulmate. I'm talking about managing days, weeks, months, and years in statistical analyses and reports! One challenge is how to number the weeks of the year. Because there are seven days in a week, 52

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Analytics | Data Visualization | Learn SAS | Programming Tips

Rick WicklinJune 16, 2025 0

Find the orthant that contains a point

This article shows how to classify a set of high-dimensional data into orthants. An orthant is the d-dimensional generalization of a quadrant. For 2-D Euclidean space, there are four quadrants, often labeled by Roman numerals I-IV. The quadrants are open sets that are defined by the signs of each coordinate

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Learn SAS | Programming Tips

Rick WicklinJune 9, 2025 0

Generate a check digit and validate a Universal Loan Identifier in SAS

This article shows how to use SAS to implement the ISO algorithm to generate (and validate) a Universal Loan Identifier (ULI). A ULI is a long string of numbers and letters that serves as a unique identifier that is used for certain financial transactions. The ISO standard ensures that banks

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Learn SAS | Programming Tips

Rick WicklinJune 2, 2025 2

The modulo operation for large integers in SAS

On social media, a SAS user reported that SAS could not compute the modulo of an extremely large integer. In SAS, the modulo operation is usually performed by using the MOD function, which computes the remainder of dividing an integer, N, by another integer, d. (In symbols, the remainder is

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Analytics | Data Visualization | Programming Tips

Rick WicklinMay 27, 2025 0

Visualize the Gini-Simpson diversity index

A previous article discusses the Gini-Simpson diversity index and how to compute it in SAS. Suppose you have a sample that contains R classes. (Classes are also called groups or categories.) Intuitively, the sample exhibits "high diversity" if the class sizes are approximately equal. The sample shows "low diversity" if

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Learn SAS | Programming Tips

Rick WicklinMay 19, 2025 1

Calculate the Gini-Simpson diversity index in SAS

An article by David Corliss in Amstat News (Corliss D. (2025) "Quantifying Diversity: Calculating the Gini-Simpson Diversity Index") discusses a new statistical measure of diversity that was adopted by the US Census Bureau. The statistic is called the Gini-Simpson diversity index. The Census Bureau has published an article about how

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Learn SAS | Machine Learning | Programming Tips

Rick WicklinApril 28, 2025 2

The SMOTE method for generating synthetic data

The Synthetic Minority Over-sampling Technique (SMOTE) was created to address class-imbalance problems in machine learning algorithms. The idea is to oversample from the rare events prior to running a machine learning classification algorithm. However, at its heart, the SMOTE algorithm (Chawla et al., 2002) is essentially a way to simulate

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Analytics | Data Visualization | Programming Tips

Rick WicklinApril 21, 2025 1

Updating old SAS programs: A case study with PROC LOESS

SAS programmers love to brag that the SAS will still run a program they wrote twenty or forty years. This is both a blessing and a curse. It's a blessing because it frees the statistical programmer from needing to revisit and rewrite code that was written long ago. It's a

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