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Dynamic Documents with R and knitr
출판사 : CRC
저 자 : Xie
ISBN : 9781482203530
발행일 : 2013-7
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 216
판매가격 : 69,000원
판매여부 : 재고확인요망
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   Dynamic Documents with R and knitr 목차
Introduction

Reproducible Research
Literature
Good and Bad Practices
Barriers

A First Look
Setup
Minimal Examples
Quick Reporting
Extracting R Code

Editors
RStudio
LYX
Emacs/ESS
Other Editors

Document Formats
Input Syntax
Document Formats
Output Renderers
R Scripts

Text Output
Inline Output
Chunk Output
Tables
Themes

Graphics
Graphical Devices
Plot Recording
Plot Rearrangement
Plot Size in Output
Extra Output Options
The tikz Device
Figure Environment
Figure Path

Cache
Implementation
Write Cache
When to Update Cache
Side Effects
Chunk Dependencies

Cross Reference 79
Chunk Reference
Code Externalization
Child Documents

Hooks
Chunk Hooks
Examples

Language Engines
Design
Languages and Tools

Tricks and Solutions
Chunk Options
Package Options
Typesetting
Utilities
Debugging
Multilingual Support

Publishing Reports
RStudio
Pandoc
HTML5 Slides
Jekyll
WordPress

Applications
Homework
Web Site and Blogging
Package Vignettes
Books

Other Tools
Sweave
Other R Packages
Python Packages
More Tools

Internals
Documentation
Closures
Implementation
A.4 Syntax
Bibliography
Index
   도서 상세설명   

The cut-and-paste approach to writing statistical reports is not only tedious and laborious, but also can be harmful to scientific research, because it is inconvenient to reproduce the results. Dynamic Documents with R and knitr introduces a new approach via dynamic documents, i.e. integrating computing directly with reporting. A comprehensive guide to the R package knitr, the book covers examples, document editors, basic usage, detailed explanations of a wide range of options, tricks and solutions, extensions, and complete applications of this package.

The book provides an overview of dynamic documents, introducing the idea of literate programming. It then explains the importance of dynamic documents to scientific research and its impact on reproducible research. Building on this, the author covers basic concepts, common text editors that support knitr, and the syntax for different document formats such as LaTeX, HTML, and Markdown before going on to discuss core functionality, how to control text and graphics output, caching mechanisms that can reduce computation time, and reuse of source code. He then explores advanced topics such as chunk hooks, integrating other languages such as Python and awk into one report in the knitr framework, and useful tricks that make it easier to write documents with knitr. Discussions of how to publish reports in a variety of formats, applications, and other tools complete the coverage.

Suitable for both beginners and advanced users, this book shows you how to write reports in simple languages such as Markdown. The reports range from homework, projects, exams, books, blogs, and web pages to any documents related to statistical graphics, computing, and data analysis. While familiarity with LaTeX and HTML is helpful, the book requires no prior experience with advanced programs or languages. For beginners, the text provides enough features to get started on basic applications. For power users, the last several chapters enable an understanding of the extensibility of the knitr package.

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