The Basics of S-PLUS (Statistics and Computing)


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History of S, R, and S-PLUS

Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden.

Publications related to R

The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed in the United States of America. Indeed, many of the recent advances in statistics have been dependent on advances in computer science and technol- ogy.

Many of the currently interesting statistical methods are computationally intensive, either because they require very large numbers of numerical computa- tions or because they depend on visualization of many projections of the data. The computationally-intensive methods of modern statistics rely heavily on the developments in statistical computing and numerical analysis generally.

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One is a characteristic of the methodology: it is computationally intensive. The other is the nature of the tools of discovery.


  • The Troubles of Journalism: A Critical Look at Whats Right and Wrong With the Press (Routledge Communication Series);
  • Mont Saint-Michel (Japanese Edition).
  • StatCompCourse < Main < Vanderbilt Biostatistics Wiki.

The computer, used to explore large numbers of scenarios, constitutes a new type of tool. Use of the computer to simulate alternatives and to present the research worker with information about these alternatives is a characteristic of the computational sciences.

Krause and Olson: The Basics of S-PLUS, 4th edition

In some ways this usage is akin to experimentation. The observations, however, are generated from an assumed model, and those simulated data are used to evaluate and study the model. Advances in computing hardware and software have changed the nature of the daily work of statisticians.

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Mixed-Effects Models in S and S-PLUS

Many statistical modelling and data analysis techniques can be difficult to grasp and apply, and it is often necessary to use computer software to aid the implementation of large data sets and to obtain useful results. S-Plus is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply a number of statistical methods, ranging from simple regression to time series or multivariate analysis.

This text offers extensive coverage of many basic and more advanced statistical methods, concentrating on graphical inspection, and features step-by-step instructions to help the non-statistician to understand fully the methodology. Gerardo , Mark D Hunter.

An Introduction to R - A Brief Tutorial for R {Software for Statistical Analysis}

Prey capture performance in hatchlings of two sibling Harmonia ladybird species in relation to maternal investment through sibling cannibalism Suzuki Noriyuki , Naoya Osawa , Takayoshi Nishida. Reciprocity and trades in wild West African chimpanzees Cristina M. Gomes , Christophe Boesch. The paradox of invasion in birds: competitive superiority or ecological opportunism?

Has the introduction of brown trout altered disease patterns in native New Zealand fish David W. Kelly , Rachel A. Paterson , Colin R. Townsend , Robert Poulin , Daniel M. Urban and peri-urban agriculture and its zoonotic risks in Kampala, Uganda Kohei Makita.

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