Advanced R

Author: Hadley Wickham
Publisher: CRC Press
ISBN: 1498759807
Format: PDF, ePub, Mobi
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An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.

Extending R

Author: John M. Chambers
Publisher: CRC Press
ISBN: 1315349876
Format: PDF, Mobi
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Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R.

Testing R Code

Author: Richard Cotton
Publisher: CRC Press
ISBN: 1315350513
Format: PDF, Kindle
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Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy for a missed minus sign to generate a false prediction that you don’t spot until it’s too late. Testing is the only way to be sure that your code, and your results, are correct. Testing R Code teaches you how to perform development-time testing using the testthat package, allowing you to ensure that your code works as intended. The book also teaches run-time testing using the assertive package; enabling your users to correctly run your code. After beginning with an introduction to testing in R, the book explores more advanced cases such as integrating tests into R packages; testing code that accesses databases; testing C++ code with Rcpp; and testing graphics. Each topic is explained with real-world examples, and has accompanying exercises for readers to practise their skills — only a small amount of experience with R is needed to get started!

Advanced R

Author: Matt Wiley
Publisher: Apress
ISBN: 1484220773
Format: PDF, ePub, Mobi
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Program for data analysis using R and learn practical skills to make your work more efficient. This book covers how to automate running code and the creation of reports to share your results, as well as writing functions and packages. Advanced R is not designed to teach advanced R programming nor to teach the theory behind statistical procedures. Rather, it is designed to be a practical guide moving beyond merely using R to programming in R to automate tasks. This book will show you how to manipulate data in modern R structures and includes connecting R to data bases such as SQLite, PostgeSQL, and MongoDB. The book closes with a hands-on section to get R running in the cloud. Each chapter also includes a detailed bibliography with references to research articles and other resources that cover relevant conceptual and theoretical topics. What You Will Learn Write and document R functions Make an R package and share it via GitHub or privately Add tests to R code to insure it works as intended Build packages automatically with GitHub Use R to talk directly to databases and do complex data management Run R in the Amazon cloud Generate presentation-ready tables and reports using R Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to take their R coding and programming to the next level.

Dynamic Documents with R and knitr Second Edition

Author: Yihui Xie
Publisher: CRC Press
ISBN: 1315360705
Format: PDF, ePub, Docs
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Quickly and Easily Write Dynamic Documents Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web pages to virtually any documents related to statistical graphics, computing, and data analysis. The book covers basic applications for beginners while guiding power users in understanding the extensibility of the knitr package. New to the Second Edition A new chapter that introduces R Markdown v2 Changes that reflect improvements in the knitr package New sections on generating tables, defining custom printing methods for objects in code chunks, the C/Fortran engines, the Stan engine, running engines in a persistent session, and starting a local server to serve dynamic documents Boost Your Productivity in Statistical Report Writing and Make Your Scientific Computing with R Reproducible Like its highly praised predecessor, this edition shows you how to improve your efficiency in writing reports. The book takes you from program output to publication-quality reports, helping you fine-tune every aspect of your report.

Statistical Computing in C and R

Author: Randall L. Eubank
Publisher: CRC Press
ISBN: 1420066501
Format: PDF
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With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather than the development and study of numerical algorithms per se. The book discusses code development in C++ and R and the use of these symbiotic languages in unison. It emphasizes that each offers distinct features that, when used in tandem, can take code writing beyond what can be obtained from either language alone. The text begins with some basics of object-oriented languages, followed by a "boot-camp" on the use of C++ and R. The authors then discuss code development for the solution of specific computational problems that are relevant to statistics including optimization, numerical linear algebra, and random number generation. Later chapters introduce abstract data structures (ADTs) and parallel computing concepts. The appendices cover R and UNIX Shell programming. Features Includes numerous student exercises ranging from elementary to challenging Integrates both C++ and R for the solution of statistical computing problems Uses C++ code in R and R functions in C++ programs Provides downloadable programs, available from the authors’ website The translation of a mathematical problem into its computational analog (or analogs) is a skill that must be learned, like any other, by actively solving relevant problems. The text reveals the basic principles of algorithmic thinking essential to the modern statistician as well as the fundamental skill of communicating with a computer through the use of the computer languages C++ and R. The book lays the foundation for original code development in a research environment.

R Graphics

Author: Paul Murrell
Publisher: CRC Press
ISBN: 9781420035025
Format: PDF, ePub, Mobi
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R is revolutionizing the world of statistical computing. Powerful, flexible, and best of all free, R is now the program of choice for tens of thousands of statisticians. Destined to become an instant classic, R Graphics presents the first complete, authoritative exposition on the R graphical system. Paul Murrell, widely known as the leading expert on R graphics, has developed an in-depth resource that takes nothing for granted and helps both neophyte and seasoned users master the intricacies of R graphics. After an introductory overview of R graphics facilities, the presentation first focuses on the traditional graphics system, showing how to work the traditional functions, describing functions that are available to produce complete plots, and how to customize the details of plots. The second part of the book describes the grid graphics system - a system unique to R and much more powerful than the traditional system. The author, who was integral in the development of the grid system, shows, starting from a blank page, how it can be used to produce graphical scenes. He also describes how to develop new graphical functions that are easy for others to use and build on. Appendices contain a brief introduction to the R system in general and discuss how the traditional and grid graphics systems can be combined. Much of the information presented in this book cannot be found anywhere else. Well ahead of the curve, particularly regarding the grid system, R Graphics will have a major impact on the future direction of statistical graphics development. The author maintains a website with more information.

Introduction to Scientific Programming and Simulation Using R Second Edition

Author: Owen Jones
Publisher: CRC Press
ISBN: 1466570016
Format: PDF, ePub, Docs
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Learn How to Program Stochastic Models Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data. The book’s four parts teach: Core knowledge of R and programming concepts How to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisation Essentials of probability, random variables, and expectation required to understand simulation Stochastic modelling and simulation, including random number generation and Monte Carlo integration In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size. Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables. Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.

Metaprogramming in R

Author: Thomas Mailund
Publisher: Apress
ISBN: 1484228812
Format: PDF, ePub
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Learn how to manipulate functions and expressions to modify how the R language interprets itself. This book is an introduction to metaprogramming in the R language, so you will write programs to manipulate other programs. Metaprogramming in R shows you how to treat code as data that you can generate, analyze, or modify. R is a very high-level language where all operations are functions and all functions are data that can be manipulated. This book shows you how to leverage R's natural flexibility in how function calls and expressions are evaluated, to create small domain-specific languages to extend R within the R language itself. What You'll Learn Find out about the anatomy of a function in R Look inside a function call Work with R expressions and environments Manipulate expressions in R Use substitutions Who This Book Is For Those with at least some experience with R and certainly for those with experience in other programming languages.

bookdown

Author: Yihui Xie
Publisher: CRC Press
ISBN: 1351792601
Format: PDF
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bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub.