Sweave
Sweave is a tool that allows to embed the R code for complete data analyses in latex documents. The purpose is to create dynamic reports, which can be updated automatically if data or analysis change. Instead of inserting a prefabricated graph or table into the report, the master document contains the R code necessary to obtain it. When run through R, all data analysis output (tables, graphs, etc.) is created on the fly and inserted into a final latex document. The report can be automatically updated if data or analysis change, which allows for truly reproducible research.
Keywords for this software
References in zbMATH (referenced in 44 articles )
Showing results 1 to 20 of 44.
Sorted by year (- Haim Bar, HaiYing Wang: Reproducible Science with LaTeX (2020) arXiv
- Michael J. Kane, Simon Urbanek: On the Programmatic Generation of Reproducible Documents (2020) arXiv
- Shi, Lei; Feng, Xiaoliang; Qi, Longxing; Xu, Yanlong; Zhai, Sulan: Modeling and predicting the influence of PM(_2.5) on children’s respiratory diseases (2020)
- Jeffrey Andrews; Jaymeson Wickins; Nicholas Boers; Paul McNicholas: teigen: An R Package for Model-Based Clustering and Classification via the Multivariate t Distribution (2018) not zbMATH
- Pedro M. Valero Mora: bookdown: Authoring Books and Technical Documents with R Markdown (2018) not zbMATH
- Coelho, L.P.: Jug: Software for Parallel Reproducible Computation in Python (2017) not zbMATH
- Anders Bilgrau; Poul Eriksen; Jakob Rasmussen; Hans Johnsen; Karen Dybkaer; Martin Boegsted: GMCM: Unsupervised Clustering and Meta-Analysis Using Gaussian Mixture Copula Models (2016) not zbMATH
- Carugo, Oliviero (ed.); Eisenhaber, Frank (ed.): Data mining techniques for the life sciences (2016)
- Hofner, Benjamin; Schmid, Matthias; Edler, Lutz: Reproducible research in statistics: a review and guidelines for the Biometrical Journal (2016)
- Maëlle Salmon; Dirk Schumacher; Michael Höhle: Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance (2016) not zbMATH
- Mathé, Ewy (ed.); Davis, Sean (ed.): Statistical genomics. Methods and protocols (2016)
- Heiberger, Richard M.; Holland, Burt: Statistical analysis and data display. An intermediate course with examples in R (2015)
- Kendall, Wilfrid S.: Introduction to coupling-from-the-past using R (2015)
- Matthias Templ; Alexander Kowarik; Bernhard Meindl: Statistical Disclosure Control for Micro-Data Using the R Package sdcMicro (2015) not zbMATH
- Ewald, Roland; Uhrmacher, Adelinde M.: SESSL: a domain-specific language for simulation experiments (2014)
- Gandrud, Christopher: Reproducible research with R and RStudio (2014)
- Philip Leifeld: texreg: Conversion of Statistical Model Output in R to LATEX and HTML Tables (2013) not zbMATH
- Toby Hocking; Thomas Wutzler; Keith Ponting; Philippe Grosjean: Sustainable, Extensible Documentation Generation Using inlinedocs (2013) not zbMATH
- Beyersmann, Jan; Allignol, Arthur; Schumacher, Martin: Competing risks and multistate models with R (2012)
- Gerlinde Dinges; Alexander Kowarik; Bernhard Meindl; Matthias Templ: An Open Source Approach for Modern Teaching Methods: The Interactive TGUI System (2011) not zbMATH
Further publications can be found at: https://www.stat.uni-muenchen.de/~leisch/papers/fl-publications.html