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About this book

S-PLUS is a powerful tool for interactive data analysis, creating graphs, and implementing customized routines. Originating as the S language of AT&T Bell Laboratories, its modern language and flexibility make it appealing to data analysts from many scientific fields. This book explains the basics of S-PLUS in a clear style at a level suitable for people with little computing or statistical knowledge. Unlike the S-PLUS manuals, it is not comprehensive, but instead introduces the most important ideas of S-PLUS through the use of many examples. Each chapter also includes a collection of exercises which are accompanied by fully worked-out solutions and detailed comments. The volume is rounded off with practical hints on how efficient work can be performed in S-PLUS. The book is well-suited for self-study and as a textbook.

Table of Contents

Frontmatter

1. Introduction

Abstract
Over the years, the S language and S-Plus have undergone many changes. Since its development in the mid-seventies, the three main authors of S, Rick Becker, John Chambers, and Allan Wilks, have enhanced the entire language considerably. All their work was done at Bell Labs with the original goal of defining a language to make it easier to do repetitive tasks in data analysis like calculating a linear model.
Andreas Krause, Melvin Olson

2. System Design

Abstract
The general layout of the S-Plus system is similar to many popular windows systems in that it has pull-down menus at the top and toolbars just below the menus. To use such a system it is useful to be a little familiar with basic point-and-click operations and how to use a mouse.
Andreas Krause, Melvin Olson

3. A First Session

Abstract
To begin the book, we introduce the most basic commands so that you can get started with S-Plus and get a feeling for how the system operates. The commands and principles discussed here may be the most basic, but they are also the most important and the ones that are used the most often. The chapter is designed to cover enough material for your first session with S-Plus. You will be surprised at how much you can do after this chapter.
Andreas Krause, Melvin Olson

4. A Second Session

Abstract
Now that you have learned some of the most basic functions available to you in S-Plus, it is time to move on to more advanced data structures that will allow you to complete complicated tasks easily. We begin with matrices and then branch out into more specialized structures: subsetting by index, and missing values. We close with a few new applications and a review of the material covered in the chapter.
Andreas Krause, Melvin Olson

5. Graphics

Abstract
Graphs are one of S-Plus’s strongest capabilities and most attractive features. You can create basic graphs by using the menu interface, but you can also do much more. We will take a look at how graphs can be created using the full functionality.
Andreas Krause, Melvin Olson

6. Exploring Data

Abstract
In the preceding chapters, we have laid the foundation for understanding the concepts and ideas of the S-Plus system. We explored basic ideas and how to use S-Plus for performing calculations, and we have seen how data can be generated, stored, and accessed. Furthermore, we also looked at how data can be displayed graphically. All this will be useful as we explore real data sets and learn how to use the existing functionality of S-Plus in this chapter. We will explore data sets that come with S-Plus, specifically the Barley and Geyser data sets.
Andreas Krause, Melvin Olson

7. Statistical Modeling

Abstract
We have now learned some elementary statistical techniques in S-Plus and the basics of graphical data analysis. The next step is to see what S-Plus has to offer in terms of modeling. Statistical modeling is one of the strongest S-Plus features because of its unified approach, wide variety of model types, and excellent diagnostic capabilities. We start with an example of how to fit a simple linear regression model and corresponding diagnostics. The example is presented with a minimum of technical explanation, designed as a quick introduction. We then formally explain the unified approach to model syntax and structure, along with comments on several of the more popular types of statistical models.
Andreas Krause, Melvin Olson

8. Programming

Abstract
Now that you have learned the elementary commands in S-Plus and many ways of applying them, it is time to discover its advanced functionalities. This chapter introduces loops, deals more intensively with writing functions, covers debugging matters, and gives a short introduction to what object-oriented programming means in the S-Plus environment.
Andreas Krause, Melvin Olson

9. Input and Output

Abstract
This is one of the most important chapters, as it is every user’s intention to analyze his or her own data. To do this, the data has to be read into the system before it can be analyzed. This chapter discusses in detail the different ways of reading and writing data.
Andreas Krause, Melvin Olson

10. Useful Hints and Techniques

Abstract
Now that you have seen elementary structures and techniques, as well as many advanced ones, we offer a few hints to make your work with S-PLUS more efficient and enjoyable.
Andreas Krause, Melvin Olson

11. Special Topics

Abstract
After having discussed some S-Plus internal topics in the preceding chapter, we now discuss some practical hints and tips more related to S-Plus and the “outer world,” the hardware on which it runs and the software with which it cooperates.
Andreas Krause, Melvin Olson

12. References

Without Abstract
Andreas Krause, Melvin Olson

Backmatter

Additional information