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The R Book

Author: Michael J. Crawley
Publisher: John Wiley & Sons
ISBN: 1118448960
Size: 42.20 MB
Format: PDF
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Hugely successful and popular text presenting an extensiveand comprehensive guide for all R users The R language is recognized as one of the most powerful andflexible statistical software packages, enabling users to applymany statistical techniques that would be impossible without suchsoftware to help implement such large data sets. R has become anessential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphicsthroughout. Introduces a clear structure with numbered section headings tohelp readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis andMeta-Analysis. Presents a fully revised and updated bibliography and referencesection. Is supported by an accompanying website allowing examples fromthe text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this textis the one that should be on your shelf. The breadth oftopics covered is unsurpassed when it comes to texts on dataanalysis in R.’ (The American Statistician, August2008) ‘The High-level software language of R is setting standardsin quantitative analysis. And now anybody can get to grips with itthanks to The R Book…’ (Professional Pensions,July 2007)

The R Software

Author: Pierre Lafaye de Micheaux
Publisher: Springer Science & Business
ISBN: 1461490200
Size: 80.32 MB
Format: PDF, ePub, Mobi
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The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

The R Primer

Author: Claus Thorn Ekstrom
Publisher: CRC Press
ISBN: 1439862087
Size: 29.13 MB
Format: PDF, ePub, Docs
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Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis. The R Primer provides a collection of concise examples and solutions to R problems frequently encountered by new users of this statistical software. Rather than explore the many options available for every command as well as the ever-increasing number of packages, the book focuses on the basics of data preparation and analysis and gives examples that can be used as a starting point. The numerous examples illustrate a specific situation, topic, or problem, including data importing, data management, classical statistical analyses, and high-quality graphics production. Each example is self-contained and includes R code that can be run exactly as shown, enabling results from the book to be replicated. While base R is used throughout, other functions or packages are listed if they cover or extend the functionality. After working through the examples found in this text, new users of R will be able to better handle data analysis and graphics applications in R. Additional topics and R code are available from the book’s supporting website at www.statistics.life.ku.dk/primer/

The R Book

Author: Barbara A. Wilson
Publisher: International Dyslexia Assoc
ISBN: 9780892140138
Size: 51.14 MB
Format: PDF
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Spatial Modeling In Gis And R For Earth And Environmental Sciences

Author: Hamid Reza Pourghasemi
Publisher: Elsevier
ISBN: 0128156953
Size: 80.32 MB
Format: PDF, ePub
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Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example

The Art Of R Programming

Author: Norman Matloff
Publisher: No Starch Press
ISBN: 1593274106
Size: 18.56 MB
Format: PDF, ePub, Mobi
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R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: –Create artful graphs to visualize complex data sets and functions –Write more efficient code using parallel R and vectorization –Interface R with C/C++ and Python for increased speed or functionality –Find new R packages for text analysis, image manipulation, and more –Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

Introducing Monte Carlo Methods With R

Author: Christian Robert
Publisher: Springer Science & Business Media
ISBN: 1441915753
Size: 38.51 MB
Format: PDF, ePub, Mobi
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This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

A Primer In Biological Data Analysis And Visualization Using R

Author: Gregg Hartvigsen
Publisher: Columbia University Press
ISBN: 0231537042
Size: 66.65 MB
Format: PDF, Mobi
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.