### About this blog

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. This blog focuses on statistical programming. It discusses statistical and computational algorithms, statistical graphics, simulation, efficiency, and data analysis. Rick is author of the books

*Statistical Programming with SAS/IML Software*and*Simulating Data with SAS*.

Follow @RickWicklin on Twitter.

**Do you have a SAS programming question?**Assistance is available! Ask SAS/IML questions at the SAS/IML Support Community. For other SAS issues, visit the SAS Support Communities.### Tags

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## Discover power laws by log-transforming data

A recent issue of Astronomy magazine mentioned Kepler's third law of planetary motion, which states "the square of a planet's orbital period is proportional to the cube of its average distance from the Sun" (Astronomy, Dec 2016, p. 17). The article included a graph (shown at the right) that shows […]

Post a Comment ## Visualize the ages of US presidents

Who was the oldest person elected president of the United States? How about the youngest? Who was the oldest when he left office? Let's look at some data. Wikipedia has a page that presents a table of the presidents of the US by age. It lists the dates for which […]

Post a Comment ## Sometimes you need to reverse the data before you fit a distribution

Occasionally on a discussion forum, a statistical programmer will ask a question like the following: I am trying to fit a parametric distribution to my data. The sample has a long tail, so I have tried the lognormal, Weibull, and gamma distributions, but nothing seems to fit. Please help!! In […]

Post a Comment ## Counting observations for which two events occur

Every year near Halloween I write an article in which I demonstrate a simple programming trick that is a real treat to use. This year's trick (which features the CMISS function and the crossproducts matrix in SAS/IML) enables you to count the number of observations that are missing for pairs […]

Post a Comment ## Loess regression in SAS/IML

A previous post discusses how the loess regression algorithm is implemented in SAS. The LOESS procedure in SAS/STAT software provides the data analyst with options to control the loess algorithm and fit nonparametric smoothing curves through points in a scatter plot. Although PROC LOESS satisfies 99.99% of SAS users who […]

Post a Comment ## What is loess regression?

Loess regression is a nonparametric technique that uses local weighted regression to fit a smooth curve through points in a scatter plot. Loess curves are can reveal trends and cycles in data that might be difficult to model with a parametric curve. Loess regression is one of several algorithms in […]

Post a Comment ## The empty-space distance plot

How far away is the nearest hospital? How far is the nearest restaurant? The nearest gas station? These are commonly asked questions whose answers depend on the location of the person asking the question. Recently I showed an algorithm that enables you to find the distance between a set of […]

Post a Comment ## Visualize a weighted regression

What is weighted regression? How does it differ from ordinary (unweighted) regression? This article describes how to compute and score weighted regression models. Visualize a weighted regression Technically, an "unweighted" regression should be called an "equally weighted " regression since each ordinary least squares (OLS) regression weights each observation equally. […]

Post a Comment ## Let PROC FREQ create graphs of your two-way tables

The recent releases of SAS 9.4 have featured major enhancements to the ODS statistical graphics procedures such as PROC SGPLOT. In fact, PROC SGPLOT (and the underlying Graph Template Language (GTL)) are so versatile and powerful that you might forget to consider whether you can create a graph automatically by […]

Post a Comment ## Distances between observations in two groups

Last week I showed how to find the nearest neighbors for a set of d-dimensional points. A SAS user wrote to ask whether something similar could be done when you have two distinct groups of points and you want to find the elements in the second group that are closest […]

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