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.
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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
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
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
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
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
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 […]Post a Comment
My son is taking an AP Statistics course in high school this year. AP Statistics is one of the fastest-growing AP courses, so I welcome the chance to see topics and techniques in the course. Last week I was pleased to see that they teach data exploration techniques, such as […]Post a Comment
Last week I showed how to compute nearest-neighbor distances for a set of numerical observations. Nearest-neighbor distances are used in many statistical computations, including the analysis of spatial point patterns. This article describes how the distribution of nearest-neighbor distances can help you determine whether spatial data are uniformly distributed or […]Post a Comment
Finding nearest neighbors is an important step in many statistical computations such as local regression, clustering, and the analysis of spatial point patterns. Several SAS procedures find nearest neighbors as part of an analysis, including PROC LOESS, PROC CLUSTER, PROC MODECLUS, and PROC SPP. This article shows how to find […]Post a Comment
Last week I wrote about how to compute sample quantiles and weighted quantiles in SAS. As part of that article, I needed to draw some step functions. Recall that a step function is a piecewise constant function that jumps by a certain amount at a finite number of points. Graph […]Post a Comment