### 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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## Simultaneous confidence intervals for a multivariate mean

Many SAS procedure compute statistics and also compute confidence intervals for the associated parameters. For example, PROC MEANS can compute the estimate of a univariate mean, and you can use the CLM option to get a confidence interval for the population mean. Many parametric regression procedures (such as PROC GLM) […]

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 ## Compute nearest neighbors in SAS

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 ## How to visualize a kernel density estimate

A kernel density estimate (KDE) is a nonparametric estimate for the density of a data sample. A KDE can help an analyst determine how to model the data: Does the KDE look like a normal curve? Like a mixture of normals? Is there evidence of outliers in the data? In […]

Post a Comment ## Use the EFFECTPLOT statement to visualize regression models in SAS

Graphs enable you to visualize how the predicted values for a regression model depend on the model effects. You can gain an intuitive understanding of a model by using the EFFECTPLOT statement in SAS to create graphs like the one shown at the top of this article. Many SAS regression […]

Post a Comment ## How to fit a variety of logistic regression models in SAS

SAS software can fit many different kinds of regression models. In fact a common question on the SAS Support Communities is "how do I fit a <name> regression model in SAS?" And within that category, the most frequent questions involve how to fit various logistic regression models in SAS. There […]

Post a Comment ## Rolling statistics in SAS/IML

Last week I showed how to use PROC EXPAND to compute moving averages and other rolling statistics in SAS. Unfortunately, PROC EXPAND is part of SAS/ETS software and not every SAS site has a license for SAS/ETS. For simple moving averages, you can write a DATA step program, as discussed […]

Post a Comment ## Banking to 45 degrees: Aspect ratios for time series plots

In SAS, the aspect ratio of a graph is the physical height of the graph divided by the physical width. Recently I demonstrated how to set the aspect ratio of graphs in SAS by using the ASPECT= option in PROC SGPLOT or by using the OVERLAYEQUATED statement in the Graph […]

Post a Comment ## Twelve posts from 2015 that deserve a second look

I began 2016 by compiling a list of popular articles from my blog in 2015. This "People's Choice" list contains many interesting articles, but some of my personal favorites did not make the list. Today I present the "Editor's Choice" list of articles that deserve a second look. I've grouped […]

Post a Comment ## Extracting elements from a matrix: rows, columns, submatrices, and indices

A matrix is a convenient way to store an array of numbers. However, often you need to extract certain elements from a matrix. The SAS/IML language aupports two ways to extract elements: by using subscripts or by using indices. Use subscripts when you are extracting a rectangular portion of a […]

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