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Modern applied statistics with S-PLUS. Includes 3.5” diskette. (English) Zbl 0806.62002
New York: Springer-Verlag. xii, 462 p. (1994).
The introductory chapter gives a quick overview of S and shows through an introductory session a bit of its power with data handling, doing statistical analyses, and producing graphics. Chapter 2 gives an overview of the S language. The first half of this chapter is rather informal whereas the second half is concerned with special points that are useful for answering “why did it do that?” questions.
Since S-PLUS provides lots of graphics facilities, just some basics are presented in the next chapter. More advanced graphics are deferred to later chapters, where they are dealt with in their statistical context. Chapter 4 is on programming in S. It surveys control structures, writing own functions etc. Also it explains how to use C and FORTRAN routines. Chapters 5 to 15 deal with special statistical areas and the implementation of related methods in S-PLUS:
Distributions and data summaries; Linear statistical models; Generalised statistical models; Robust statistics; Nonlinear regression models; Modern regression; Survival analysis; Multivariate analysis; Tree-based models; Time series; and Spatial statistics. Through these chapter- headings the broad range of the functions already available in S-PLUS for doing statistical analyses can be imagined.
Version 3.2 of S-PLUS is essential for using the data and functions on the diskette enclosed. For UNIX users only are the directories nnet and spatial. Nnet contains functions for neural networks (described in the chapter on modern regression), and the specialist methods of spatial statistics are given in the related directory. S itself includes only one spatial interpolation method.

62-04 Software, source code, etc. for problems pertaining to statistics
62-00 General reference works (handbooks, dictionaries, bibliographies, etc.) pertaining to statistics
62-07 Data analysis (statistics) (MSC2010)
68U99 Computing methodologies and applications
65C99 Probabilistic methods, stochastic differential equations