About

Dirk Eddelbuettel is a quantitative software engineer and data scientist with extensive experience in research, development, and trading. He serves as an adjunct Clinical Professor in Statistics at the University of Illinois Urbana-Champaign, where he created and teaches the course STAT 447: Data Science Programming Methods. Dirk has been contributing to open source projects, particularly Debian and R, since the 1990s. He maintains numerous Debian packages and develops or maintains several projects centered around R, often involving C++ and utilizing Rcpp, a package he initiated and leads. Additionally, he is a co-creator of the Rocker Project, which integrates Docker with R, and has recently worked on the r2u project. His work on Rcpp culminated in a book published in Springer's useR! series. Dirk's contributions extend to various publications, talks, workshops, and lectures, reflecting his active engagement in the data science and software engineering communities.

Research topics

• Computer Science
• Climatology
• Geology
• Mathematics
• Biology
• Geography
• Engineering
• Statistics
• Meteorology
• Environmental science
• Physical geography

Selected publications

• zigg: Lightweight Interfaces to the 'Ziggurat' Pseudo Random Number Generator

  2025-01-31 · 1 citations

  datasetOpen access1st authorCorresponding

  The 'Ziggurat' pseudo-random number generator (or PRNG), introduced by Marsaglia and Tsang (2000, &lt;<a href="https://doi.org/10.18637%2Fjss.v005.i08" target="_top">doi:10.18637/jss.v005.i08</a>&gt;) and further improved by Leong et al (2005, &lt;<a href="https://doi.org/10.18637%2Fjss.v012.i07" target="_top">doi:10.18637/jss.v012.i07</a>&gt;), offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from 'C/C++' code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package. The implementation is influenced by our package 'RcppZiggurat' which offers a comparison among multiple alternative implementations but presented here in a lighter-weight implementation that is easier to use by other packages. The PRNGs provided are generally faster than the ones in base R: on our machine, the relative gains for normal, exponential and uniform are on the order of 7.4, 5.2 and 4.7 times faster than base R. However, these generators are of potentially lesser quality and shorter period so if in doubt use of the base R functions remains the general recommendation.

  PublisherOA PDFDOI

• RcppMagicEnum: 'Rcpp' Bindings to 'Magic Enum' 'C++' 'Enum' Support

  2024-08-19

  datasetOpen access1st authorCorresponding

  The header-only modern 'C++' template library 'Magic Enum' for static reflection of 'enums' (to string, from string, iteration) is provided by this package. More information about the underlying library can be found at its repository at &lt;<a href="https://github.com/Neargye/magic_enum" target="_top">https://github.com/Neargye/magic_enum</a>&gt;.

  PublisherOA PDFDOI

• Polly: An R package for genotyping microsatellites and detecting highly polymorphic <scp>DNA</scp> markers from short‐read data

  Molecular Ecology Resources · 2024-02-01 · 1 citations

  articleOpen access

  Highly polymorphic markers, such as microsatellites, are invaluable for the study of natural populations. However, contemporary methods for genotyping highly polymorphic variants have serious drawbacks that impede their efficiency. We created Polly, an R package with C++ source code that uses Illumina short-read data to genotype microsatellites, detect highly polymorphic variants and identify clusters of highly polymorphic SNPs, indels and microsatellites. We tested Polly on short-read data from Xiphophorus birchmanni (Teleostei: Poeciliidae) and Arabidopsis thaliana, finding it to be efficient and accurate both for microsatellite genotyping and polymorphic marker detection. This program can be applied to any diploid population for which there exists short-read data and at least one scaffolded reference genome.

  PublisherOA PDFDOI

• ciw: Watch the CRAN Incoming Directories

  2024-03-13

  datasetOpen access1st authorCorresponding

  Directory reads and summaries are provided for one or more of the subdirectories of the &lt;<a href="https://cran.r-project.org/incoming/" target="_top">https://cran.r-project.org/incoming/</a>&gt; directory, and a compact summary object is returned. The package name is a contraption of 'CRAN Incoming Watcher'.

  PublisherOA PDFDOI

• mlpack 4: a fast, header-only C++ machine learninglibrary

  The Journal of Open Source Software · 2023-02-01 · 28 citations

  articleOpen access

  For over 15 years, the mlpack machine learning library has served as a “swiss army knife’’ for C++-based machine learning (Curtin et al., 2013). Its efficient implementations of common and cutting-edge machine learning algorithms have been used in a wide variety of scientific and industrial applications. This paper overviews mlpack 4, a significant upgrade over its predecessor (Curtin et al., 2018). The library has been significantly refactored and redesigned to facilitate an easier prototyping-to-deployment pipeline, including bindings to other languages (Python, Julia, R, Go, and the command line) that allow prototyping to be seamlessly performed in environments other than C++.

  PublisherOA PDFDOI

• CRAN Task Views: The Next Generation

  arXiv (Cornell University) · 2023-05-27 · 2 citations

  preprintOpen access

  CRAN Task Views have been available on the Comprehensive R Archive Network since 2005. They provide guidance about which CRAN packages are relevant for tasks related to a certain topic, and can also facilitate automatic installation of all corresponding packages. Motivated by challenges from the growth of CRAN and the R community as a whole since 2005, all of the task views infrastructure and workflows were rethought and relaunched in 2021/22 in order to facilitate maintenance and to foster deeper interactions with the R community. The redesign encompasses the establishment of a group of CRAN Task View Editors, moving all task view sources to dedicated GitHub repositories, adopting well-documented workflows with a code of conduct, and leveraging R/Markdown files (rather than XML) for the content of the task views.

  PublisherOA PDFDOI

• crc32c: Cyclic Redundancy Check with CPU-Specific Acceleration

  2023-05-08

  datasetOpen access1st authorCorresponding

  Hardware-based support for 'CRC32C' cyclic redundancy checksum function is made available for 'x86_64' systems with 'SSE2' support as well as for 'arm64', and detected at build-time via 'cmake' with a software-based fallback. This functionality is exported at the 'C'-language level for use by other packages. 'CRC32C' is described in 'RFC 3270' at &lt;<a href="https://datatracker.ietf.org/doc/html/rfc3720" target="_top">https://datatracker.ietf.org/doc/html/rfc3720</a>&gt; and is based on 'Castagnoli et al' &lt;<a href="https://doi.org/10.1109%2F26.231911" target="_top">doi:10.1109/26.231911</a>&gt;.

  PublisherOA PDFDOI

• RcppInt64: 'Rcpp'-Based Helper Functions to Pass 'Int64' and 'nanotime' Values Between 'R' and 'C++'

  2023-09-05

  datasetOpen access1st authorCorresponding

  'Int64' values can be created and accessed via the 'bit64' package and its 'integer64' class which package the 'int64' representation cleverly into a 'double'. The 'nanotime' packages builds on this to support nanosecond-resolution timestamps. This packages helps conversions between 'R' and 'C++' via several helper functions provided via a single header file. A complete example client package is included as an illustration.

  PublisherOA PDFDOI

• tinythemes: Lightweight Repackaging of 'Themes' for 'ggplot2'

  2023-12-18

  datasetOpen access1st authorCorresponding

  Themes for 'ggplot2' are a convenient way to style plots. The 'hrbrthemes' package contains a particularly nice one, but brings along a significant tail of dependencies. So this (currently experimental) package brings along just the 'theme_ipsum_rc' theme using the 'Roboto' 'Condensed' font. Should the font not be installed on your system, see the help in the package 'hrbrthemes' on how to install 'Roboto Condensed'. Note that 'hrbrthemes' is now archived at CRAN.

  PublisherOA PDFDOI

• RcppFastAD: 'Rcpp' Bindings to 'FastAD' Auto-Differentiation

  2023-02-27

  datasetOpen access1st authorCorresponding

  The header-only 'C++' template library 'FastAD' for automatic differentiation &lt;<a href="https://github.com/JamesYang007/FastAD" target="_top">https://github.com/JamesYang007/FastAD</a>&gt; is provided by this package, along with a few illustrative examples that can all be called from R.

  PublisherOA PDFDOI

Frequent coauthors

• James Balamuta

  12 shared

• Romain François

  5 shared

• Carl Boettiger

  University of California, Berkeley

  5 shared

• Conrad Sanderson

  5 shared

• Joshua Ferreri

  University of Colorado Denver

  4 shared

• Meilin Yan

  Beijing Technology and Business University

  4 shared

• Nathalie Villa‐Vialaneix

  Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

  3 shared

• Wush Wu

  3 shared

Education

• Ph.D. Mathematical Economics and Econometrics, GREQAM

  Ecole des Hautes Etudes en Sciences Sociales

  1997