A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.

Modern Applied Statistics with S (Statistics and Computing)

Computers & Technology

Ripley, B.D.

Venables, W.N.

Programming

Springer

S is a high-level language for manipulating, analysing and displaying data. It forms the basis of two highly acclaimed and widely used data analysis software systems, the commercial S-PLUS® and the Open Source R. This book provides an in-depth guide to writing software in the S language under either or both of those systems. It is intended for readers who have some acquaintance with the S language and want to know how to use it more effectively, for example to build re-usable tools for streamlining routine data analysis or to implement new statistical methods. One of the outstanding strengths of the S language is the ease with which it can be extended by users. S is a functional language, and functions written by users are first-class objects treated in the same way as functions provided by the system. S code is eminently readable and so a good way to document precisely what algorithms were used, and as much of the implementations are themselves written in S, they can be studied as models and to understand their subtleties. The current implementations also provide easy ways for S functions to call compiled code written in C, Fortran and similar languages; this is documented here in depth. Increasingly S is being used for statistical or graphical analysis within larger software systems or for whole vertical-market applications. The interface facilities are most developed on Windows® and these are covered with worked examples. The authors have written the widely used Modern Applied Statistics with S-PLUS, now in its third edition, and several software libraries that enhance S-PLUS and R; these and the examples used in both books are available on the Internet. Dr. W.N. Venables is a senior Statistician with the CSIRO/CMIS Environmetrics Project in Australia, having been at the Department of Statistics, University of Adelaide for many years previously. Professor B.D. Ripley holds the Chair of Applied Statistics at the University of Oxford, and is the author of four other books on spatial statistics, simulation, pattern recognition and neural networks. Both authors are known and respected throughout the international S and R communities, for their books, workshops, short courses, freely available software and through their extensive contributions to the S-news and R mailing lists.

S Programming (Statistics and Computing)

Venables, William

Programming Languages

This book is designed for specialists needing an introduction to statistical inference in spatial statistics and its applications. One of the author's themes is to show how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of the lack of a unique asymptotic setting in spatial problems. Throughout, he discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarizing of images.

Statistical Inference for Spatial Processes

Science & Math

Mathematics

Cambridge University Press

This book is designed for specialists needing an introduction to statistical inference in spatial statistics and its applications. One of the author's themes is to show how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of the lack of a unique asymptotic setting in spatial problems. Throughout, he discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarizing of images.

Venables, W.N. N.

Software

S is a high-level language for manipulating, analysing and displaying data. It forms the basis of two highly acclaimed and widely used data analysis software systems, the commercial S-PLUS® and the Open Source R. This book provides an in-depth guide to writing software in the S language under either or both of those systems. It is intended for readers who have some acquaintance with the S language and want to know how to use it more effectively, for example to build re-usable tools for streamlining routine data analysis or to implement new statistical methods.  One of the outstanding strengths of the S language is the ease with which it can be extended by users. S is a functional language, and functions written by users are first-class objects treated in the same way as functions provided by the system. S code is eminently readable and so a good way to document precisely what algorithms were used, and as much of the implementations are themselves written in S, they can be studied as models and to understand their subtleties. The current implementations also provide easy ways for S functions to call compiled code written in C, Fortran and similar languages; this is documented here in depth.  Increasingly S is being used for statistical or graphical analysis within larger software systems or for whole vertical-market applications. The interface facilities are most developed on Windows® and these are covered with worked examples.  The authors have written the widely used Modern Applied Statistics with S-PLUS, now in its third edition, and several software libraries that enhance S-PLUS and R; these and the examples used in both books are available on the Internet.  Dr. W.N. Venables is a senior Statistician with the CSIRO/CMIS Environmetrics Project in Australia, having been at the Department of Statistics, University of Adelaide for many years previously.  Professor B.D. Ripley holds the Chair of Applied Statistics at the University of Oxford, and is the author of four other books on spatial statistics, simulation, pattern recognition and neural networks. Both authors are known and respected throughout the international S and R communities, for their books, workshops, short courses, freely available software and through their extensive contributions to the S-news and R mailing lists.

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Books by Ripley, B.D.

See the best price to sell, buy, or rent books by Ripley, B.D.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Modern Applied Statistics with S (Statistics and Computing)

S Programming (Statistics and Computing)

Statistical Inference for Spatial Processes

Statistical Inference for Spatial Processes

Modern Applied Statistics with S (Statistics and Computing)

S Programming (Statistics and Computing)