Introduction | DEoptim structure | C / C++ changes | R changes | Auxiliary files | Performance | Summary

Introduction | Eigen classes | Some simple examples | Least squares solutions | Delayed evaluation | Sparse matrices | Summary

Introduction | Sections | Title formats | Metropolis title formats | Elements | Typography | Font feature test | Lists | Animation (using \LaTeX\ ) | Animation (using RMarkdown, plus one \LaTeX\ trick) | Figures (using \LaTeX) | Tables (using \LaTeX}) | Blocks | Math | Line plots | Bar charts | Quotes | References | Notes | Conclusion | Summary | Backup slides | R Appendix: R Figure Example | R Appendix: R Table Example

Overview and Introduction | Data Structure Example Five: Sorted Sets | Communication Example: Publish/Subscribe | Application Example: Hash R Objects | Summary

Overview

Motivation

Overview | Armadillo | RcppArmadillo | Kalman Filtering Example | Empirical Speed Comparison | Conclusion

Introduction | Sparse Matrix

If you must use RcppClassic | You should not use RcppClassic

Implementation of the temporal types

Introduction | Motivation: fastLm | Vectors | Matrices | Using in your package | Using with | Using with Rcpp Attributes | Summary

Introduction | DieHarder | Examples | Current Limitations and Future Research | Conclusion

About | Part I Data | Part II: Base Plots | Part III: Using ggplot

Protocol Buffers | Basic use: Protocol Buffers and R | Utilities | Advanced Features | Other approaches | Plans for future releases | Acknowedgements

Introduction | Protocol Buffers | Basic usage: Messages and descriptors | Under the hood: S4 classes and methods | Type coercion | Converting R data structures into Protocol Buffers | Application: Distributed data collection with MapReduce | Application: Data interchange in web services | Summary | The rexp.proto schema descriptor

Example proto file | Read proto description files | Create a message | Serialize a message to a file or binary connection | Read a message from a file or binary connection} | Get/Set fields | Message methods | More info

title: "tidyCpp Motivation"author: "Dirk Eddelbuettel"date: "Initial version November 2020; Updated August 2021 and November 2025"css: "water.css" | Introducing tidyCpp | Snippet One: dimnames | Using the C API for R | Using tidyCpp | Snippet Two: convolution | Snippet Three: uchardet | Snippet Four: Rolling min and max | Using the Rcpp version | PROTECT and UNPROTECT | Discussion | Summary

Setting up your package | Including the header files | Defining the search type | Building an index | Searching for nearest neighbors | Further information

Using Attributes | Package Development

Introduction | Extending Rcpp::wrap | Extending Rcpp::as | Summary

Getting started | Compiling and Linking | Examples | Support | Known Issues

Introduction | First Steps with | A first function using | Extending via its API | Extending via the API of | Data Driven Performance Decisions with | Random Numbers within : An Example of Rcpp Sugar | Translating Code from into : Bootstrap Example | Using as an Interface to External Libraries: Exploring Linear Algebra Extensions | in Packages | Conclusion

Introduction | The Rcpp API | R and C++ data interchange | Function calls | Using code `inline' | Using Standard Template Library algorithms | Error handling | Performance comparison | On-going development | Summary

Introduction

Motivation | Rcpp modules | Using modules in other packages | Future extensions | Known shortcomings | Summary

Introduction | Using Rcpp.package.skeleton | Using modules | Further examples | Other compilers | Summary

Important Notes

Motivation | Operators | Functions | Performance | Implementation | Summary

title: "Calculating SHA1 hashes with digest() and sha1()"author: "Thierry Onkelinx and Dirk Eddelbuettel"date: "Written Jan 2016, updated Jan 2018 and Oct 2020"css: "water.css" | Short intro on hashes | Difference between digest() and sha1() | Choosing digest() or sha1() | Creating a sha1 method for other classes | How to | summary.lm | lm | Using hashes to track changes in analysis

Introduction | YAML Content | author | address | lead_author_surnames | doi_footer | abstract | acknowledgements | keywords | Options | fontsize | one_column | lineno | one_sided | numbersections | secnumdepth | skip_final_break | bibliography | watermark | footer_contents | date_subtitle | document_date | Code | Knitr | Pandoc | Environments | Standard LaTeX | figure* | widetext | Other Help | RMarkdown | LaTeX

title: "Combining Drat and Travis CI"author: "Colin Gillespie and Dirk Eddelbuettel"date: "Written 2015-04-14, updated 2021-03-29"css: "water.css" | What is Travis CI? | Preliminaries | Workflow | Example deploy.sh script

title: "Drat Basics for Package Authors: Distributing Packages"author: "Dirk Eddelbuettel"date: "2015-05-24"css: "water.css" | Drat Overview | Case 1: Using GitHub | GitHub as a Web Server | Place Files into the Local Repo | GitHub and Travis Integration | Case 2: Using Another Server or Local Storage | Summary

title: "Introduction to RcppSpdlog"author: "Dirk Eddelbuettel"date: "Initial version dated October 2020. Expanded November 2022."css: "water.css" | Introducing RcppSpdlog | Initial example: Basics | Second example: Showcase | Third example: Colour | Fourth Example: Dedicated R Logger | R-specific sink | Stopwatch | Log-Level | Fifth Example: Initialization | Sixth Example: Compile-time Selection | Seventh Example: Access From R | Eight Example: Access From Another R Package | Nineth Example: More compact C++ Access | Tenth Example: More compact R Access | Eleventh Example: Stopwatch Support in R and C++ | Conclusion

An Introduction to tint | Margin Examples | Margin Figures | Full Width Figures | Main Column Figures | Font Extensions | Citations, Code, Tables and More | Citations | Code | Tables

An Introduction to tint | Margin Examples | Margin Figures | Full Width Figures | Main Column Figures | Font Extensions | Citations, Code, Tables and More | Citations | Code | Tables

title: "Introducing Rblpapi"author: "Dirk Eddelbuettel"date: "2015-08-13"css: "water.css" | Introduction | Usage | Package Load | Connecting | bdp: Bloomberg Data Point | bds: Bloomberg Data Set | bdh: Bloomberg Data History | getBars: OHLCV Aggregates | getTicks: Transactional Tick Data | fieldSearch: Query For Fields | beqs: Bloomberg EQS Queries | Acknowledgements | Legal

title: "Drat Frequently Asked Questions"author: "Dirk Eddelbuettel"date: "2016-10-27"css: "water.css" | What is drat? | Why use drat? | Where is drat? | What other documentation is there? | Why the focus on GitHub? | What if not GitHub? | Why could install_github be wrong? | Can drat work with binaries? | Can drat act as an Additional_repositories ? | What about the miniCRAN package? | Is there a suggested commit message convention?

title: "Minimal Set of binnmu Packages"subtitle: "Combining the R and Debian package systems"author: "Dirk Eddelbuettel"date: "First version 2017-Jul-16; this version 2017-Aug-05"css: "water.css" | Step 0: Problem Definition | Upstream Change | Impact | Step 1: Reverse Dependencies of R | Fresh Debian unstable session | Update Debian | Launch R | All Candidates | Compiled Packages | Version check | Step 2: Grep | Step 3: Finalize | Summary | Acknowledgements | History | See Also

title: "Drat Basics for Package Users: Installing or Updating Packages"author: "Dirk Eddelbuettel"date: "2015-05-24"css: "water.css" | Drat Overview | Case 1: Using GitHub | Case 2: Using Another Repo | Summary

title: Drat Step-By-Stepauthor: Roman Hornung and Dirk Eddelbuetteldate: "Written 2021-Apr-04, updated 2021-Jul-09"css: "water.css" | Overview, Scope and Background | Steps | Prepare the dependent package | Create the drat repository | Create a local copy of your fork | Ensure you have the drat package | Finalising | Test it | Use the drat repo | Additional step | Summary

title: "Why Drat?"author: "Steven Pav and Dirk Eddelbuettel"date: "2015-03-27"css: "water.css" | Demo | Use cases | My wish list

title: "Littler Examples"author: "Dirk Eddelbuettel"date: "Originally written 2015-10-28; Updated 2017-12-10, 2018-05-24, 2019-01-06, 2019-06-09 and 2020-06-16"css: "water.css" | Overview | Simple Direct Command-line Use | install.r: Direct CRAN Installation | install2.r: With Cmdline Parsing | Installing From Sources | check.r: Simple Checker | rcc.r: R CMD check wrapper | build.r: Building Packages | installGithub.r: GitHub install | update.r: CRAN package update | knit.r: Calling knitr | roxy.r: Running roxygen | compAttr.r: Compiling Attributes | render.r: Render Markdown

title: "Littler FAQ"author: "Dirk Eddelbuettel"date: "2019-03-23, updated 2020-06-16"css: "water.css" | Well, why? | No Printing | No .Renviron | Lower-case / upper-case | Adding the binary to your path

RcppMsgPack | Installation: | Example: