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› Find signed collectible books: 'Modern Applied Statistics with S (Statistics and Computing)'
S-Plus is a powerful environment for statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-Plus to perform statistical analyses and provides both an introduction to the use of S-Plus and a course in modern statistical methods. The aim of the book is to show how to use S-Plus as a powerful and graphical system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-Plus, and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets.
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› Find signed collectible books: 'Modern Applied Statistics with S-PLUS (Statistics and Computing) (v. 1)'
S is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas that have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S environments to perform statistical analyses and provides both an introduction to the use of S and a course in modern statistical methods. Implementations of S are available commercially in S-PLUS(R) workstations and as the Open Source R for a wide range of computer systems. The aim of this book is to show how to use S as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-PLUS or R and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state of the art approaches to topics such as linear, nonlinear and smooth regression models, tree-based methods, multivariate analysis, pattern recognition, survival analysis, time series and spatial statistics. Throughout modern techniques such as robust methods, non-parametric smoothing and bootstrapping are used where appropriate. This fourth edition is intended for users of S-PLUS 6.0 or R 1.5.0 or later. A substantial change from the third edition is updating for the current versions of S-PLUS and adding coverage of R. The introductory material has been rewritten to emphasis the import, export and manipulation of data. Increased computational power allows even more computer-intensive methods to be used, and methods such as GLMMs, MARS, SOM and support vector machines are considered.
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› Find signed collectible books: 'S Programming (Statistics and Computing)'
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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› Find signed collectible books: 'Statistical Inference for Spatial Processes'
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.
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