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Rick WicklinDecember 2, 2024 3

A historical method of generating random normal variates

Decades ago, it was a challenge to generate (pseudo-) random numbers that had good statistical properties. The proliferation of desktop computers in the 1980s and '90s led to many advances in computational mathematics, including better ways to generate pseudorandom variates from a wide range of probability distributions. (For brevity, I

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Analytics | Learn SAS | Programming Tips

Rick WicklinNovember 20, 2024 1

Order two-dimensional vectors by using angles

Order matters. The order of variables in tables and rows of a correlation matrix can make a big difference in how easy it is to observed correlations between variables or groups of variables. There are many ways to order the variables, but this article shows how to display the variables

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Learn SAS | Programming Tips

Rick WicklinNovember 13, 2024 4

A vector-to-string function for SAS IML

A previous article discusses the MakeString function, which you can use to convert an IML character vector into a string. This can be very useful. When I originally wrote the MakeString function, I was disappointed that I could not vectorize the computation. Recently, I learned about the COMBL function in

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Learn SAS | Programming Tips

Rick WicklinNovember 4, 2024 0

Levy flight and vectorizing a simulation in SAS

A previous article shows a simulation of two different models of a foraging animal. The first model is a random walk, which assumes that the animal chooses a random direction, then takes a step that is distributed according to a Gaussian random variable. In the second model, the animal again

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Data Visualization | Learn SAS | Programming Tips

Rick WicklinOctober 28, 2024 3

Automate the creation of a range attribute map in SAS

In SAS, range attribute maps enable you to specify the range of values that determine the colors used for graphical elements. There are various examples that use the GTL to define a range attribute map, but fewer examples that show how to use a range attribute map with PROC SGPLOT.

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Analytics | Programming Tips

Rick WicklinOctober 21, 2024 1

The correlogram: Visualize correlations by fitting angles

A common way to visualize the sample correlations between many numeric variables is to display a heat map that shows the Pearson correlation for each pair of variables, as shown in the image to the right. The correlation is a number in the range [-1, 1], where -1 indicated perfect

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Learn SAS | Programming Tips

Rick WicklinOctober 16, 2024 0

Run-time variations of the INPUT and PUT functions in SAS

The INPUT function and PUT function in SAS are used to apply informats and formats (respectively) to data. For both functions, you must know in advance which informat or format you want to apply. For brevity, let's consider only applying a format. To use the PUT function, you must know

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Learn SAS | Programming Tips

Rick WicklinOctober 14, 2024 3

Understand the PUT and INPUT functions in SAS

In SAS, the INPUT and PUT functions are powerful functions that enable you to convert data from character type to numeric type and vice versa. They work by applying SAS formats or informats to data. You cannot fully understand the INPUT and PUT functions without understanding formats and informats in

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Analytics | Learn SAS | Programming Tips

Rick WicklinOctober 7, 2024 0

The three-sigma rule

A remarkable result in probability theory is the "three-sigma rule," which is a generic name for theorems that bound the probability that a univariate random variable will appear near the center of its distribution. This article discusses the familiar three-sigma rule for the normal distribution, a less-familiar rule for unimodal

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Learn SAS | Programming Tips

Rick WicklinSeptember 30, 2024 2

Programming the formulas for an ANOVA in SAS

In practice, there is no need to remember textbook formulas for the ANOVA test because all modern statistical software will perform the test for you. In SAS, the ANOVA procedure is designed to handle balanced designs (the same number of observations in each group) whereas the GLM procedure can handle

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