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SAS/IML and SAS/IML Studio Papers and Presentations
SAS Stat Studio: A Programming Environment for High-End Data Analysts
Wicklin, Rick; SAS Institute, 2008
Abstract
SAS Stat Studio 3.1 is new statistical software in SAS 9.2 that is designed to meet the needs of high-end data analysts? innovative problem solvers who are familiar with SAS/STAT and SAS/IML but need more versatility to try out new methods. Stat Studio provides a rich programming language, called IMLPlus, that blends an interactive matrix language (IML) with the ability to call SAS procedures as functions and to create customized dynamic graphics. For standard tasks, Stat Studio provides the same interactive graphics and statistical capabilities available in SAS/INSIGHT, and so it serves as a programmable successor to SAS/INSIGHT.
With Stat Studio, you can build on your familiarity with SAS/STAT or SAS/IML to write programs that explore data, fit models, and relate the results to the data with linked graphics. You can programmatically add legends, curves, maps, or other custom features to plots. You can write interactive analyses that respond to your input to analyze only selected subsets of the data. You can move seamlessly between programming and interactive analysis.
A previous paper (Wicklin and Rowe, 2007) introduced Stat Studio and presented examples of the point-and-click interface. This paper focuses on programming aspects of Stat Studio; the goal is to demonstrate techniques that are straightforward in Stat Studio but might be difficult to implement in other software. Not all programming statements are described in detail in this paper; for more information see the Stat Studio documentation.
The main ideas in this paper are illustrated by using meteorological data. The paper consists of three main sections. Section 1 describes the data, creates graphs to visualize the data, and introduces simple programming statements to draw features on the graphs. These features enhance the understanding of relationships between variables. Section 2 describes how you can call SAS procedures from IMLPlus and add results from the procedures to an interactive plot. Section 3 describes two advanced programs: one uses animation to graphically compare statistical results across BY groups; the other demonstrates a bootstrap method for estimating the distributions of statistics.
This paper is not a tutorial, but reading this paper can help you understand several analytical techniques that you can program in Stat Studio. Appendix A includes a list of frequently used programming statements and a description of where you can find additional documentation about programming Stat Studio.
